高分辨率红外成像中的图像处理算法研究
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摘要
近年来,红外成像技术取得了很大进步,在国防建设和国民经济各领域得到广泛的应用,如目标跟踪、成像制导和环境监测等。受探测器结构、制造工艺以及材料等因素限制,红外探测器存在非均匀性噪声和欠采样等问题,导致温度分辨率和空间分辨率不高,影响了红外系统的成像质量,限制了红外整机的探测距离,成为红外成像技术发展的瓶颈。高分辨率成像一直是红外成像领域研究的重点,不仅在理论上具有重要意义,实用中也有迫切需求。本文以提高红外成像温度分辨率和空间分辨率为目标,主要围绕红外成像的非均匀性校正和超分辨率重建展开,具体内容包括：
1)红外焦平面阵列探测器非均匀性校正技术。从红外焦平面阵列、读出电路和环境温度三个方面讨论了非均匀性的产生机理,建立了探测器响应与环境温度的指数关系模型。针对探测器非均匀性随着时间漂移的问题,提出三种改进的场景非均匀性校正算法。结合红外焦平面阵列探测器输出信号的时间和空间特性,利用读出电路相邻通道差异的高斯分布,估计通道放大器引起的固定竖条噪声,提出将单帧迭代和黑体标定相结合的非均匀性校正算法。改进的神经网络非均匀性校正构造了基于读出电路的隐含层期望值,并应用LMS原理自适应调整步长以提高收敛速度。根据恒定统计理论,提出一种时域高通非均匀性校正中的“鬼影”抑制算法,将已估计偏置参数作为先验条件判断当前像素是否参与当前帧偏置参数的计算,解决了固定阈值场景适应性差的问题。
2)微扫描超分辨率成像技术。研究了微扫描成像的图像处理技术,包括微扫描图像预滤波和图像插值。在图像预滤波部分,针对P-M方程解的病态性,提出改进的各向异性扩散滤波算法。算法结合像素梯度和局部方差构造了噪声低敏感性的扩散系数,该系数从理论上满足Charbonnier等提出的构造准则。在图像插值部分,提出改进的边缘保持图像插值和Lagrange多项式图像插值算法。边缘保持图像插值算法建立了局部标准差边缘模型,将图像分为平滑和边缘区域,平滑区域以像素邻域差值作为加权系数实现图像插值,边缘区域选用最大梯度方向的像素实现图像插值。Lagrange多项式图像插值算法将图像划分成多个的同性区域,在各个同性区域内自适应调整Lagrange的阶数,完成图像插值。
3)多帧图像的超分辨率重建技术。围绕图像配准和图像重建问题展开研究。在图像配准部分,基于数学形态学和Mallat多分辨率分析理论,提出一种多尺寸模板配准算法,算法有效抑制了噪声影响；在图像重建部分,从Bayes随机场角度,基于Huber-Markov正则化模型,提出一种梯度阈值自适应调整的MAP超分辨率重建算法。
实验测试和仿真表明,本文提出的技术与现有技术相比具有一定的优势。这些新技术已经应用到制冷和非制冷凝视型红外成像系统以及红外微扫描成像系统中,得到了满意的成像效果,展现了这些技术在提高红外图像质量方面的实用价值。
Infrared imaging technique has achieved much progress and been applied to military and civilian fields in recent years, such as target tracking, imaging guidance, environmental monitoring and so on. Due to the structure of detector, manufacture technology, material etc, there are some problems in infrared detector, such as nonuniformity noise and undersampling, which result in low temperature resolution and spatial resolution, bad imaging quality and short detecting distance. High resolution imaging, which is theoretically important as well as practically urgent, is an active topic in infrared imaging region during recent years. For improving temperature resolution and spatial resolution of infrared imaging, nonunifomity correction and superresolution of infrared imaging are mainly discussed. The studies are carried out in the following aspects:
1) Nonuniformity correction technique of infrared focal plane array (IRFPA) detector. The mechanism of nonuniformity was discussed from IRFPA, readout circuit and environmental temperature. The exponential relationship between detector response and environmental temperature was established. For solving the nonuniformity drift in time, three novel sence-based NUC algorithms were proposed. Aiming at the time and spatial features of signal output, a nonuniformity correction algorithm based on iterative theory and blackbody calibration was presented. The fixed stripe noise was estimated using Gaussian distribution of the difference of adjacent readout channels. New expectation estimation was constructed and the step value was adjusted adaptively based on the LMS theory in the improved neural network nonuniformity correction. A ghosting eliminated technique was proposed based on high-pass in time domain and low-pass in spatial domain. Accordding to constant-statistics theory, current pixel whether was used for computing offset parameter or not depending on the existed offset estimation.
2) Microscan superresolution imaging technique. We discussed the image processing of microscan including pre-filtering and interpolate construction. In the pre-filtering part, aiming at ill-conditioned problem of the P-M equation, an improved anisotropic diffusion algorithm was presented. Based on pixel gradient and local variance characteristics, a diffusion coefficient was established which satisfies the condition of diffusion coefficient presented by Charbonnier. In the interpolation reconstruction part, an edge-preserved interpolation and an improved Lagrange interpolation algorithm were proposed, respectively. According to local root-mean-square edge model, the image was divided into smoothness and edge regions. The interpolation was carried out by using adjacent pixels in the smoothness region and the pixel of greatest gradient direction in the edge region, respectively. Improved Lagrange interpolation algorithm divided image into multi-isotropy regions, the exponent number of Lagrange equation was adjusted self-adaptively in every isotropy region.
3) Multiframe superresolution reconstruction. Our discussion focuses on image registration and reconstruction. In the image registration part, a multi-scale templates registration algorithm was proposed based on morphological and Mallat multi-resolution analysis theories, which can effectively eliminate the noise. In the image reconstruction part, from Bayes random field angle, a self-adaptive threshold MAP superresolution reconstruction was proposed based on Huber-Markov model of regularization.
Experimental tests and simulations show the proposed algorithms are superior compared with existed algorithms. These new technologies have been applied to the imported cool and uncool staring infrared imaging system and microscan imaging system, which achieve promising results. All of these show these key techniques have real value for improving the quality of infrared image.
1)红外焦平面阵列探测器非均匀性校正技术。从红外焦平面阵列、读出电路和环境温度三个方面讨论了非均匀性的产生机理,建立了探测器响应与环境温度的指数关系模型。针对探测器非均匀性随着时间漂移的问题,提出三种改进的场景非均匀性校正算法。结合红外焦平面阵列探测器输出信号的时间和空间特性,利用读出电路相邻通道差异的高斯分布,估计通道放大器引起的固定竖条噪声,提出将单帧迭代和黑体标定相结合的非均匀性校正算法。改进的神经网络非均匀性校正构造了基于读出电路的隐含层期望值,并应用LMS原理自适应调整步长以提高收敛速度。根据恒定统计理论,提出一种时域高通非均匀性校正中的“鬼影”抑制算法,将已估计偏置参数作为先验条件判断当前像素是否参与当前帧偏置参数的计算,解决了固定阈值场景适应性差的问题。
2)微扫描超分辨率成像技术。研究了微扫描成像的图像处理技术,包括微扫描图像预滤波和图像插值。在图像预滤波部分,针对P-M方程解的病态性,提出改进的各向异性扩散滤波算法。算法结合像素梯度和局部方差构造了噪声低敏感性的扩散系数,该系数从理论上满足Charbonnier等提出的构造准则。在图像插值部分,提出改进的边缘保持图像插值和Lagrange多项式图像插值算法。边缘保持图像插值算法建立了局部标准差边缘模型,将图像分为平滑和边缘区域,平滑区域以像素邻域差值作为加权系数实现图像插值,边缘区域选用最大梯度方向的像素实现图像插值。Lagrange多项式图像插值算法将图像划分成多个的同性区域,在各个同性区域内自适应调整Lagrange的阶数,完成图像插值。
3)多帧图像的超分辨率重建技术。围绕图像配准和图像重建问题展开研究。在图像配准部分,基于数学形态学和Mallat多分辨率分析理论,提出一种多尺寸模板配准算法,算法有效抑制了噪声影响；在图像重建部分,从Bayes随机场角度,基于Huber-Markov正则化模型,提出一种梯度阈值自适应调整的MAP超分辨率重建算法。
实验测试和仿真表明,本文提出的技术与现有技术相比具有一定的优势。这些新技术已经应用到制冷和非制冷凝视型红外成像系统以及红外微扫描成像系统中,得到了满意的成像效果,展现了这些技术在提高红外图像质量方面的实用价值。
Infrared imaging technique has achieved much progress and been applied to military and civilian fields in recent years, such as target tracking, imaging guidance, environmental monitoring and so on. Due to the structure of detector, manufacture technology, material etc, there are some problems in infrared detector, such as nonuniformity noise and undersampling, which result in low temperature resolution and spatial resolution, bad imaging quality and short detecting distance. High resolution imaging, which is theoretically important as well as practically urgent, is an active topic in infrared imaging region during recent years. For improving temperature resolution and spatial resolution of infrared imaging, nonunifomity correction and superresolution of infrared imaging are mainly discussed. The studies are carried out in the following aspects:
1) Nonuniformity correction technique of infrared focal plane array (IRFPA) detector. The mechanism of nonuniformity was discussed from IRFPA, readout circuit and environmental temperature. The exponential relationship between detector response and environmental temperature was established. For solving the nonuniformity drift in time, three novel sence-based NUC algorithms were proposed. Aiming at the time and spatial features of signal output, a nonuniformity correction algorithm based on iterative theory and blackbody calibration was presented. The fixed stripe noise was estimated using Gaussian distribution of the difference of adjacent readout channels. New expectation estimation was constructed and the step value was adjusted adaptively based on the LMS theory in the improved neural network nonuniformity correction. A ghosting eliminated technique was proposed based on high-pass in time domain and low-pass in spatial domain. Accordding to constant-statistics theory, current pixel whether was used for computing offset parameter or not depending on the existed offset estimation.
2) Microscan superresolution imaging technique. We discussed the image processing of microscan including pre-filtering and interpolate construction. In the pre-filtering part, aiming at ill-conditioned problem of the P-M equation, an improved anisotropic diffusion algorithm was presented. Based on pixel gradient and local variance characteristics, a diffusion coefficient was established which satisfies the condition of diffusion coefficient presented by Charbonnier. In the interpolation reconstruction part, an edge-preserved interpolation and an improved Lagrange interpolation algorithm were proposed, respectively. According to local root-mean-square edge model, the image was divided into smoothness and edge regions. The interpolation was carried out by using adjacent pixels in the smoothness region and the pixel of greatest gradient direction in the edge region, respectively. Improved Lagrange interpolation algorithm divided image into multi-isotropy regions, the exponent number of Lagrange equation was adjusted self-adaptively in every isotropy region.
3) Multiframe superresolution reconstruction. Our discussion focuses on image registration and reconstruction. In the image registration part, a multi-scale templates registration algorithm was proposed based on morphological and Mallat multi-resolution analysis theories, which can effectively eliminate the noise. In the image reconstruction part, from Bayes random field angle, a self-adaptive threshold MAP superresolution reconstruction was proposed based on Huber-Markov model of regularization.
Experimental tests and simulations show the proposed algorithms are superior compared with existed algorithms. These new technologies have been applied to the imported cool and uncool staring infrared imaging system and microscan imaging system, which achieve promising results. All of these show these key techniques have real value for improving the quality of infrared image.
引文
[1]范晋祥,张渊.新概念军用红外成像系统的发展.红外与激光工程,2008,37(3)：386～390
[2]屈惠明.红外成像电子学理论及其关键技术研究.南京：南京理工大学博士学位论文,2007
[3]蒋一明,王克勇,郑链,等.坦克目标的红外成像建模与仿真.红外技术,2008,30(1)：39-42
[4]KEITH L. Challenges in the evolution of advanced imaging systems. Proceedings of SPIE,2007,6714:1-7
[5]何伟,焦斌斌,薛惠琼,等.非冷红外焦平面阵列进展.电子工业专业设备,2008,37(5)：18～23
[6]张敬贤,李玉丹,金伟其.微光与红外成像技术.北京：北京理工大学出版社.1995
[7]金伟其,刘广容,白廷柱,王霞.夜视领域几个热点技术的进展及分析.光学技术,2005,31(3)：405～509
[8]简耀波.红外图像处理中的关键算法研究.武汉.华中科技大学博士学位论文,2009
[9]江照意.典型目标场景的红外成像仿真研究.杭州.浙江大学博士学位论文,2007
[10]孙恋君.微测辐射热计阵列性能及信号处理电路研究.南京.南京理工大学博士学位论文,2008
[11]邢素霞.非制冷红外热成像系统研究.南京.南京理工大学博士学位论文,2005
[12]王晓宇.红外图像分析关键技术研究.武汉.华中科技大学博士学位论文,2008
[13]常本康,蔡毅.红外成像阵列与系统.北京：科学出版社,2006
[14]Stuart Kleinfelder, Alison Hottes, Roger Fabian W. Pease. Focal plane array readout integrated circuit with per-pixel analog-to-digital and digital-to-analog conversion. Proceedings of SPIE,2000,4028:139-147
[15]Sang-Gu Kang, Doo H. Woo, Hee C. Lee. Infrared focal plane array readout integrated circuit with on-chip 14 b A/D converter. Proceedings of SPIE. 2004,5234:287-295
[16]Chih-Cheng Hsieh, Chung-Yu Wu. Focal-plane-arrays and CMOS Readout Techniques of Infrared Imaging Systems. IEEE Transactions on Circuits and Systems for Video Technology,1997,7(4):594-605
[17]Marion B. Reine. Review of HgCdTe photodiodes for IR detection. Proceedings of SPIE,2000,4028:320-330
[18]Philippe M. Tribolet, Patricia Costa, P. Fillon, et al. Large staring arrays at SOFRADIR. Proceedings of SPIE,2003,4820:418-428
[19]Sarath D. Gunapala, Sumith V. Bandara, John K. Liu. Recent developments and applications of quantum well infrared photodetector focal plane arrays, Proceedings of SPIE,2000,4028:262-275
[20]A. M. Filachev, V.P. Ponomarenko, I. I. Taubkin, M. B. Ushakova. Infrared focal plane arrays:state of the art and development trends. Proceedings of SPIE, 2003,5126:52-85
[21]K. Buskila, S. Towito, E. Shmuel, R. Levi, N. Kopeika, K. Krapels, R. G. Driggers, R.H. Vollmerhausen, C.E. Halford. Atmospheric modulation transfer function in the infrared. Appl Opt.,2004,43(2):471-482
[22]张毅,柏连发,陈钱,顾国华.红外焦平面微扫描空间分辨率性能分析与估算.红外与激光工程,2009,38(2)：221-225
[23]罗海波,史泽林.红外成像制导技术发展现状与展望.红外与激光工程,2009,38(4)：565～573
[24]王成刚,孙浩,李敬国,朱西安.双色碲镉汞红外焦平面探测器发展现状.激光与红外,2009,39(4)：367～371
[25]陈丽菊,刘巍.近红外光谱分析技术及发展前景.现代物理知识,2006,18(2)：10～11
[26]Richard Blackwell, Steven Geldart, Margaret Kohin, et al, Recent technology advancements and applications of advanced uncooled imagers, Proceedings of SPIE., 2004,5406:422-427
[27]蔡毅.对第三代热成像技术的思考,展望2010年中国夜视技术.中国兵工学会第四界夜视技术专业委员会主办,广西北海,2003.11
[28]吴诚,苏君红,潘顺臣,冯生荣,金伟其.对中波与长波红外焦平面热成像的一些探讨.红外技术.,2002,24(2)：6～8
[29]蔡毅,汤锦亚.对红外热成像技术发展的几点看法红外技术.2000,22(2)：2～6
[30]张天序,施长城,李洁珺,刘慧娜,袁雅婧,周泱.红外焦平面阵列非均匀性自适应校正算法研究进展.红外与毫米波学报,2007,26(6)：409～413
[31]石岩,张天序,李辉,曹治国.一种考虑红外焦平面器件非线性响应的非均匀校正方法.红外与毫米波学报,2004,23(4)：251～256
[32]屈惠明,陈钱.红外焦平面阵列二元非线性的非均匀性理论模型.电子学报, 2008,36(11)：2150～2153
[33]白俊奇,陈钱,钱惟贤,屈惠明,王娴雅,左超.基于环境温度的红外焦平面阵列非均匀性校正.红外与毫米波学报,2010,29(1)49～52
[34]Hardie R C, Hayat M M, Amstong E. Scene-based nonuniformity correction using video sequences and registration. Applied Optics,2000,39(8):1241-1250
[35]Ratliff B M, Hayat M M, Tyo H S, Generalized algebraic scene-based nonuniformity correction algorithm. Journal of the Optical Society of America A,2005,22:239-249
[36]Narendra P M, Foss N A. Shutterless fixed pattern noise correction for infrared imaging arrays. Proceedings of SPIE,1981,282:44-51
[37]Scribner D A, Sakady K A, Caufield J T. Nonuniformity correction for staring IR focal Plane arrays using scene-based techniques, Infrared Detectors and Focal Plane Arrays, SPIE,1990,1308:224-233
[38]Scribner D A, Sakady K A, Kruer M R. Adaptive retina-like preprocessing for imaging detector arrays. Proc. IEEE,1993:1955-1960
[39]Harris H G, Chiang Y M. Nonuniformity correction using the constant-statistics constraint analog and digital implementations. Proceedings of SPIE,1997, 3061:895-905
[40]Harris H G, Chiang Y M. Minizing the ghosting artifact in scene-based nonunifomity correction. Proceedings of SPIE,1998,3377:106-113
[41]赖睿,杨银堂.场景自适应的红外焦平面阵列非均匀性校正新方法.西安电子科技大学学报,2009,36(2)：228～232
[42]Weixian Qian, Qian Chen, Guo hua Gu. Space low-pass and temporal high-pass nonuniformity correction algorithm. Optical Review,2010,17(1):24-29
[43]Hayat M M, Torres S N, Amstrong, Stephen C Cain, Brian Yasuda. Statistical algorithm for nonuniformity correction in focal-plane arrays. Applied Optics,1999, 38(8):772-780
[44]Torres S N, Pezoa J E, Hayat M M. Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form. Applied Optics, 2003,42(29):5872-5881
[45]Torres S N, Hayat M M. Kalman filtering for adaptive nonuniformity correction in infrared focal-plane arrays. Journal of the Optical Society of America A, 2003,20:470-480
[46]Pezoa J E, Hayat M M, Torres S N, Multimodel kalman filtering for adaptive nonuniformity correction in infrared sensors. Journal of the Optical Society of America A,2006,23:1282-1291
[47]Jorge E Pezoa,Majeed M Hayat, Sergio N Torres, Md Saifur Rahman. Multimodel Kalman filtering for adaptive nonuniformity correction in infrared sensors. J. Opt. Soc. Am.A.2006,23(6):1282-1291
[48]周慧鑫,魏亚姣,秦翰林,王炳健.基于非线性模型的卡尔曼滤波非均匀性校正算法.光学学报,2009,29(2)378～381
[49]张天序,石岩,曹治国.红外焦平面非均匀性噪声的空间频率特性及空间自适应非均匀性校正方法.改进红外与毫米波学报,2005,24(4)：255～260
[50]Shehadeh M, Kuybeda O. Robust nonuniformity correction in infrared images based on global motion. IEEE 25th Convention of Electrical and Electronics Engineers in Israel,2008:275-279
[51]Pipa D, da Silva E, Pagliari C, Perez M M. Joint bias and gain nonuniformity correction of infrared videos using tensorial-RLS technique.200916th IEEE International Conference on Image Processing (ICIP),2009:3897-3900
[52]Cohen M, Cauwenberghs GFloating-gate adaptation for focal-plane online nonuniformity correction. IEEE Transactions on Circuits and Systems II:Analog and Digital Signal Processing,2001:83-89
[53]Weixian Qian, Qian Chen, Guohua Gu, Zhiqiang Guan. Correction method for stripe nonuniformity. Applied Optics,2010,49(10):1764-1773
[54]吴新社,蔡毅.红外凝视成像系统中的光学微扫描技术.红外与毫米波学报,2007,26(1)：10～14
[55]吴新社,范乃华,李龙,徐世春,蔡毅.铁电型非制冷红外焦平面探测器的调制器设计,红外技术,2007,29(6)：333～336
[56]吴新社,蔡毅,范乃华,李龙.铁电型非制冷红外焦平面探测器的斩波器设计.红外与激光工程,2006,增刊
[57]K. Awamoto, U. Ito, H. Ishizaki. Resolution improvement for HgCdTe IRCCD. Infared Detectors and Focal Plane Arrays II, SPIE,1992,1689
[58]J. Fortin, P. Chevertte. Realization of a fast microscannning device for infrared focal plane arrays. SPIE,2743,185
[59]R. K. McEwen, P. A. Mannig. European Uncooled thermal imaging technology. BAE SYSTEMD Infared Limited, March 2000
[60]W. Cabanski, R. Breiter, K. H. Mauk. Miniaturized high performance starring thermal imaging system. SPIE,2000,4028
[61]沈卫.法国泰勒斯公司推出新型武器热瞄具.轻兵器,2005
[62]H. S. Kim, C. W. Kim, S. M. Hong. Compact mid-wavelength infrared zoom camera with 20:1 zoom range and automatic athermalization. Optical Engineering,2002 41(7):1661-1667
[63]Alain Bergeron, Loic Le Noc, Bruno Tremblay, Francois Lagace, Luc Mercier, Francois Duchesne, Linda Marchese, Julie Lambert, Michel Hacob, Martin Morissette, Hubert Jerominek. Flexible 640×480 pixel infrared camera module for fast prototyping. Proceedings of SPIE,2009,7481:74810L-1-74810L-9
[64]首山雄,陈进勇.微扫描多帧平滑FPN提高CMOS图像传感器信噪比.浙江大学学报,2002,36(6)：621～623
[65]金伟其,王春勇,张楠,王岭雪,卢萍.扫描型焦平面热成像系统的亚像元处理算法研究.红外与毫米波学报,2005,24(4)：261-264
[66]张楠,金伟其,苏秉华,刘扬阳.高分辨力红外热图像重建算法的进展及研究.兵工学报,2005,26(2)：173～176
[67]Eric Kaltenbacher, Russell C. Hardie. High resolution infrared image reconstruction using multiple, low resolution, aliased frames. SPIE,2751, pp:142-152
[68]Stone H S, Orchard M T, Ee-Chien Chang and Martucci S A. A fast direct Fourier-based algorithm for subpixel registration of images. IEEE Transactions on Geoscience and Remote Sensing,2001,39(10):2235-2243
[69]Hassan Foroosh (Shekarforoush), Josiane B Zerubia, Senior Member, IEEE, and Marc Berthod. Extension of phase correction to subpixel registration. IEEE,2002, pp:188-200
[70]Eun Sil Lee and Moon Gi Kang. Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration. IEEE Transactions on Image Processing,2003,12(7):826-837
[71]徐超,金伟其,李雅琼,王霞.一种改进的凝视焦平面探测器亚像元成像处理算法.电子学报,2007,35(8)：1608～1611
[72]Manuel Guizar-Sicairos, Samuel T Thurman, and James R Fienup. Efficient subpixel image registration algorithms. Optics Letters,2008,33(2):156-158
[73]金伟其,陈翼男,王霞,李雅琼,王岭雪.考虑探测器填充率及微扫描对位偏差的扫描型亚像元热成像算法.红外与毫米波学报,2008,27(4)：308～312
[74]高美静,金伟其,王霞,于杰.光学微扫描显微热成像扫描零点定标方法研究.光学学报,2009,29(8)：2175～2179
[75]韩玉兵.图像及视频序列的超分辨率重建.南京：东南大学博士学位论文,2005
[76]何宇清.图像超分辨率重建关键技术研究.天津：天津大学博士学位论文,2007
[77]陈艳.图像超分辨率重建关键技术的研究.上海：上海交通大学博士学位论文,2007
[78]丁海勇.遥感图像超分辨率重建技术研究.徐州：中国矿业大学博士学位论文,2008
[79]宋锐.视频和图像序列的超分辨率重建技术研究.西安西安电子科技大学博士学位论文,2009
[80]H. A Brown. Effect of truncation on image enhancement by prolate spheroidal function. Journal of the Optical Society of America A,1969,59:228-229
[81]B. R. Hunt, P. Sementill. Description of a poisson imagery super-resolution algorithm, Astronomical Data Analysis Software and System. Astronomical Society of the Pacific, San Framcisco,1992
[82]C. K. Rusforth. In image reconstruction, theory and application. Academic Press, New York,1987
[83]Kim S P, Bose N K, Valenzuela H M. Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Transactions on Acoustics, Speech, and Signal Processing,1990,38(6):1013-1027
[84]Kim S P, Su W. Recursive high-resolution reconstruction of blurred multiframe images. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing, Toronto Canada, May 1991,4:2977-2980
[85]Bose N K, Kim H C, Valenzuela H M. Recursive total least squares algorithm for image reconstruction from noisy, undersampled multiframes. Multidimensional Systems and Signal Processing,1993,4(3):253-268
[86]Tekalo A M, Ozekan M K, Sezan M I. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, San Francisco CA,1992,111:169-172
[87]Keren D, Peleg S, Brada R. Image sequence enhancement using subpixel displacements. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 1988:742-746
[88]Schuler J M, Howard J G, Warren P R, etc. Resolution enhancement through TARID processing. In Proceedings of SPIE-the International Society for Optical Engineering, San Jose, CA, United states,2002, pp872-876
[89]Schuler J M, Howard J G, Warren P R, etc. TARID-based image superresolution. in Proceedings of SPIE-the International Society for Optical Engineering, Orlando, Fl, United states,2002, pp247-254
[90]Aizawa K, Komatsu T, Saito T. A scheme for acquiring very high resolution images using multiple camers. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Proceedings, San Francisco, CA Mar.1992,3:289-292
[91]Shmuel P, Danny K, Limor S. Improving image resolution using subpixel moton. Pattern Recognition Letter,1987,5(3):223-226
[92]Irani M, Peleg S. Super resolution from image sequences. In Proceeding of the 10th International Conference on Pattern Recognition, Atlantic City, NJ, June 1990, 2:115-120
[93]Irani M, Peleg S. Improving resolution by image registration. CVGIP:Graphical Models and Image Processing,1991,53(3):231-239
[94]Mann S, Pickard R W. Virtual Bellows:Construting high quality stills from video. In Proceedings of the IEEE international Conference on Image Processing, Austin, TX, 1994,363-367
[95]Tom B C, Katsaggelos A K. Multi-channel image identification and restoration using the expectation maximization algorithm. In Applications of Digital Image Processing XVII, San Diego, CA, July 1994, vol.2298 of Proceedings of theSPIE,316-331
[96]Tom B C, Katsaggelos A K. Reconstruction of a high-resolution image by simultaneous registration, restoration and interpolation of low-resolution images. In Proceedings of the IEEE International Conference Image Processing, Washington DC,1995, 2:539-542
[97]Tom B C, Katsaggelos A K, Galatsanos N P. Reconstruction of a high resolution image from registration and restoration of low resolution images. In Proceedings of the IEEE International Conference Image Processing, Austin, TX,1994,Ⅲ:553-557
[98]Tom B C, Katsaggelos A K. A iterative algorithm for improving the resolution of video sequences. In Visual Communications and Image Processing of Proceedings of the SPIE,1996,2727,1430-1438
[99]Schultz R R, Stevenson R L. Extraction of high-resolution frames from video sequences. Image Processing, IEEE Transactions on,1996,5(6):996-1011
[100]Hardie R C, Barnard K J, Armstrong E E. Joint MAP registration and high-resolution image estimation using a sequence of Undersampled images. IEEE Trans. On Image Processing,1997,6(12):1621-1633
[101]Cheeseman P, Kanefsky B, Kraft R, etc. Super-resolved surface reconstruction from multiple images[DB/OL]. http://hanson.gmu.edu/image.pdf,1994
[102]Elad M, Feuer A. Restoration of a single superresolution image from several blurred, noisy and undersampled measured images. IEEE Transactions on Image Processing, 1997,6(12):1646-1658
[103]Elad M, Feuer A. Super-resolution reconstruction of image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(9):817-834
[104]Sementilli P J, Nadar M S, Hunt B R. Empirical evaluation of a bound on image superresolution performance. Proceedings of SPIE-the International Society for Optical Engineering,1994,2302:178-187
[105]Lorette A, Shekarforoush H, Zerubia J. Super-resolution with adaptive regularization. In IEEE International Coference on Image Processing, Los Alamitos, CA, USA, 1997:169-172
[106]Farsiu S, Robinson M D, Elad M etc, Fast and robust multiframe super resolution. IEEE Transactions on Image Processing, Oct,2004,13(10):1327-1344
[107]Stark H, Oskoui P. High-resolution image recovery from image-plane arrays, using convex projections. Journal of the Optical Society of America A,1989, 6(11):1715-1726
[108]Patti A J, Altunbasak Y. Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants. IEEE Transactions on Image Processing,2001,10(1):179-186
[109]Patti A J, Sezan M I, Tekalp A M. Robust methods for high-quality still from interlaced video in the presence of dominant motion. IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342
[110]Eren P E, Sezan M I, Tekalp A M. Robust object-based high-resolution image reconstruction from low-resolution video. IEEE Transactions on Image Processing, 1997,6(10):1446-1451
[111]Russell C. Hardie, Kenneth J. Barnard, John G. Bognar, Ernest E. Armstrong, Edward A. Watson. High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system. Optical Engineering,1997, pp1-27
[112]Mohammad S. Alam, John G. Bognar, Russell C. Hardie, Brian J. Yasuda. Infared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames. IEEE Transactions on Instrumentation and Measurement,2000,49(5):915-923
[113]Russell C. Hardie, Douglas R. Droege. A map estimator for simultaneous superresolution and detector nonunifomity correction. EURASIP Journal on Advances inSignal Processing,2007, ID89354, ppl-11
[114]Wenyi Zhao, Chao Zhang. Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion. Journal of the Optical Society of America A, 2008,25(7):1668-1681
[115]Tuan Q. Pham, Lucas J. Van Vliet, Klamer Schutte, Robust super-resolution by minimizing a Gaussian-weighted L2 Error Norm.4th AIP International Conference and the 1st Congress of the IPIA, Journal of Physics.:Conference Series124(2008)012037,pp1-20
[116]Irene G. Karybali, Emmanouil Z. Psarakis, Kostas Berberidis, Georgios D. Evangelidis. An efficient spatial domain technique for subpixel image registration. Signal Processing:Image Communication,2008,23:711-724
[117]张晓飞,基于DSP的红外焦平面阵列非均匀性校正技术研究.重庆：重庆大学,2002
[118]陈永甫.红外辐射红外器件与典型应用.北京：电子工业出版社,2004
[119]王义玉.红外探测器.北京：兵器工业出版社,1993
[120]Jan Baars. Max Schulz. Performance characteristics, measurement procedures and figures of merit for infrared focal plane arrays. Proceedings of SPIE. 1995(2470):141-155
[121]W. A. Cabanski and M. J. Schulz. Electronic and optical properties of silicide/silicon ir detectors. Proceedings of SPIE.1991(1484):81-97
[122]陈西曲.非致冷红外焦平面的读出电路及测试系统研究.武汉华中科技大学博士学位论文,2007
[123]Hsieh C C, Wu C Y, Jih F W. Focal-plane-arrays and CMOS readout techniques of infrared imaging systems. IEEE Trans. On CSVT,1997,7:594-605
[124]Zhao Y, Mao M Y, Horowitz R. Optomechanical uncooled infared imaging systems:Design, microfabrication and performance. J. Microelectromechanical Sys, 2002,11:136-146
[125]米本和也(著),陈榕庭,彭美桂(译)CCD/CMOS图像传感器基础与应用.北京：科学出版社,2005
[126]隋修宝,陈钱,顾国华.环境温度对红外图像非均匀性影响的研究.光子学报,2008,37(12)：2572～2575
[127]Pipa D, Da Silva E, Pagliari C, Perez M M. Joint bias and gain nonuniformity correction of infrared videos using tensorial-RLS technique. Image Processing(ICIP), 16th IEEE International Conference,2009, pp:3897-3900
[128]Shehadeh M, Kuybeda O. Robust nonuniformity correction in infrared images based on global motion. Electrical and Electronics Engineers in Israel, IEEE 25th Convention of,2008, pp:275-279
[129]Huixin Zhou, Hanlin Qin, Rui Lai, Shangqian Liu. Adaptive filtering for nonuniformity correction in infrared focal plane arrays. Infrared and Millimeter Waves 15th International Conference on Terahertz Electronics. IRMMWTHZ Joint 32nd International Conference on,2007, pp:510-511
[130]Yongjin Liu, Hong Zhu, Yigong Zhao. New scene-based nonuniformity correction algorithm of infrared focal plane arrays. Image and Signal Processing and Analysis, ISPA 2007 5th International Symposium on,2007, pp:274-277
[131]Grzegorz Bieszczad, Tomasz Sosnowski, Henryk Madura, Mariusz Kastek, Jaroslaw Barela. Adaptable infrared image processing module implemented in FPGA. Infrared Technology and Applications ⅩⅩⅩⅥ, Proc. of SPIE,2010,7660,pp:76603Z-1-10
[132]Jonah C McBride, Magnus S Snorrason. Improving scene-based non-uniformity correction for infrared images using frequency domain processing. Thermosense ⅩⅩⅩⅠ, Proc. of SPIE,2009,7299,pp:729903-1-11
[133]Liquan Dong, Xiaohua Liu, Yuejin Zhao, Mei Hui, Xiaoxiao Zhou. Scene-based nonuniformity correction algorithm for MEMS-based un-cooled IR image system. Infrared Systems and Photoelectronic Technology Ⅳ, Proc. of SPIE,2009,7419, pp74190Y-1-12
[134]Daniel Pipa, Eduardo A B, Carla Pagliari, Marcelo M Perez. Joint bias and gain nonuniformity correction of infrared videos using tensorial-rls technique. ICIP2009. IEEE,2009, pp:3897-3900
[135]Gyong Jin Oh, Lyang June Kim, Sue Ho Sheen, Gyou Phyo Koo, Sang Hun Jin, Bo Yeon Yeo, Jone Ho Lee. Implementation of real time nonuniformity correction with multiple NUC tables using FPGA in an uncooled imaging system. Infrared Technology and Applications ⅩⅩⅩⅤ, Proc. of SPIE,2009,7298,pp:72982E-1-8
[136]Zhenguo Liu, Xiaomei Hu, Jin Lu. An improved neural network non-uniformity correction for IRFPA. International Symposium on Photoelectronic Detection and Imaging, SPIE,2009,7383:pp:738330-1-8
[137]Douglas R Droege. Scene-based nonuniformity correction using texture-based adaptive filtering. Infrared Technology and Applications ⅩⅩⅩⅢ, Proc. of SPIE, 2007,6542, pp:65423R-1-12
[138]Sebastian E Godoy, Sergio N Torres, Jorge E Pezoa, Majeed M Hayat, Qi Wang. Nonuniformity correction algorithm based on a noise-cancellation system for infrared focal-plane arrays. Infrared Technology and Applications ⅩⅩⅩⅢ, Proc. of SPIE,2007,6542, pp:65423S-1-11
[139]徐田华,赵亦工.基于场景的红外焦平面非均匀校正技术研究.红外与毫米波学报,2004,23(4)：257～261
[140]Scribner D, Sarkady K, Kruer M. Adaptive nonuniformity correction for infared focal plane arrays using neural network. Proc of Infared Sensors:Detectors, Electronics, and Signal Processing:1541. San Diego:SPIE,1991:100-109
[141]董立泉,金伟其,隋婧.基于场景的红外焦平面阵列非均匀性校正算法综述.光学技术,2008,34(suppl.)：112-122
[142]孙恋君,张俊举,王世允,常本康,钱芸生.非制冷微测辐射热计探测器工作温度特性研究.红外与毫米波学报,2007.26(3)：232～236
[143]Balaji Narayanan. Nonuniformity correction for focal plane arrays and partition based superresolution of video with application to an infared imaging system. Dayton, the Doctor Dissertation of University of Dayton,2005
[144]刘永进,朱红,赵亦工.基于红外焦平面阵列读出结构的非均匀性校正算法.光学精密工程,2008,16(1)：128～133
[145]黄倩,王岩飞,张冰尘,苗慧.一种新的各向异性扩散SAR相干斑抑制算法.电子学报,2006,34(9)：1553-1557
[146]Lai Rui, Yang Yin Tang, Zhou Duan, Li Yue Jin. Improved neural network based scene-adaptive nonuniformity correction method for infrared focal plane arrays. Applied Optics,47(24):4331-4335
[147]J Kim, C W, Lee, J K Lee, J S Hwang, J H Park. Comparsion of adaptive systems for noise reduction in speech performance. In Proceeding of the IEEE 38th Southeastern Symposium on System Theory,2006,pp:123-127
[148]D G Manoakis, V K Ingle, S M Kogon. Statistical and adaptive signal processing(McGraw-Hill,2000).
[149]John G Harris, Yu-Ming Chiang. Nonuniformity correction of infrared image sequences using the constant-statistics constraint. IEEE Transactions on Image Processing,1999,8(8):1148-1151
[150]Esteban Vera R, Sergio Torres I. Ghosting reduction in adaptive nonuniformity correction of infared focal-plane array image sequences. IEEE,2003,111001-1004
[151]Narendra P M, Foss N A. Shutterless fixed pattern noise correction for infared imaging array. SPIE,1981,282:44-51
[152]John G Harris, Yu-Ming Chiang. Minimizing the "ghosting" artifact in scene-based nonuniformity correction. Part of the SPIE Conference on Infrared Imaging Systems: Design, Analysis, Modeling and Testing IX, Orlando,1998,3377:106-113
[153]Zhang Tianxu, Shi Yan. Edge-directed adaptive nonuniformity correction for staring infrared focal plane arrays. Optical Engineering,2006,45(1):1-11
[154]张天序,石岩.红外焦平面阵列非均匀性自适应校正算法中目标退化与伪像的消除方法.红外与毫米波学报,2005,24(5)：335～340
[155]刘会通,马红伟.自适应非均匀性校正中“鬼影”问题的分析.红外技术,2003,25(5)：30～32
[156]徐雨明,文双春.数字图像插值算法的分析与实现.福建电脑,2007,1：90～91
[157]刘洪臣,冯勇,杨旭强.基于双三次B样条曲面亚像元图像插值方法.哈尔滨工业大学学报,2007,39(7)：1121～1124
[158]江铭炎,李兴江,袁东风.2*图像插值放大处理的方法.山东大学学报(理学版),2003,38(3)：79～81
[159]符祥,郭宝龙.图像插值技术综述.计算机工程与设计,2009,30(1)：141～144
[160]Edward A Watson, Robert A Muse, Fred p Blommel. Aliasing and blurring in microscanned imagery. Infrared Imaging Systems, SPIE,1992,1689,pp:242-250
[161]S P Kim, N k Bose, H M Valenzuela, Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Trans. Acoust. Speech Signal Process.1990,38(6):1013-1027
[162]Joseph C Gillette, Thomas M Stadtmiller. Aliasing reduction in staring infrared imagers utilizing subpixel techniques. Optical Engineering,1995,34(11):3130-3137
[163]隋修宝.非制冷凝视热像仪成像理论以及关键技术研究.南京：南京理工大学博士学位论文,2009
[164]李兰兰.基于偏微分方程的图像复原和增强算法研究.南京：东南大学博士学位论文,2004
[165]Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. On PAMI,1990,12(7):629-639
[166]Gilboa G, Sochen N, Zeevi Y Y. Image enhancement and dinoising by complex diffusion processing. IEEE Trans. On PAMI,2004,26(8):1020-1036
[167]严家斌,刘贵忠.一种新的各向异性扩散时间尺度估计方法.计算机工程,2008,34(2)：43～45
[168]Weeratunga S, Kamath C. Comparison of PDE-based non-linear anistropic diffusion techniques for image denoising. Proc of SPIE,2003,5014:201-212
[169]Shih A C, Liao H M, Lu C S. A new iterated two-band diffusion equationtheory and its application. IEEE Transaction on Image Processing,2003,12(4):466-476
[170]H Bruder, R Raupach, E Klotz, K Stierstorfer, T Flohr. Spatio-temporal filtration of dynamic CT data using diffusion filters. Physics of Medical Imaging, Proc of SPIE, 2009,7258,pp:725857-1-10
[171]Hongmin Zhang, Xiaohua Lv. Modified robust anisotropic diffusion denoising technique with regularized Richardson-lucy deconvolution fro two-photon microscopic images. Optical Engineering,2008,47(4):047004-1-8
[172]Jinshan Tang, Qingling Sun. A 3-D anisotropic diffusion filter for speckle reduction in 3-D ultrasound images. Three-Dimensional Imaging Metrology, SPIE,2009, 7239,pp:72390T-1-9
[173]Zhentian Wang, Li Zhang, Yuxiang Xing, Ziran Zhao. PDE regularization for Bayesian reconstruction of emission tomography. Physics of Medical Imaging, Proc. of SPIE,2008,6913,pp:69132X-1-8
[174]Eric J Wharton, Karen A Panetta, Sos S Agaian. Edge preserving image enhancement using anisotropic diffusion. Image Processing:Algorithms and Systems VI, SPIE, 2008,6812,pp:681218-1-10
[175]张相芬,DTI图像去噪方法研究.上海：上海交通大学博士学位论文,2008
[176]王毅,张良培,李平湘.各向异性扩散平滑滤波的改进算法.中国图象图形学报,2006,11(2)：210～216
[177]Catte F, Lions P L, Morel J. Image Selective smoothing and edge detection by nonlinear diffusion. SIAM Journal on Numerical Analysis,1992,29(3):845-866
[178]孙兆林MATLAB 6.X图像处理.北京清华大学出版社,2002
[179]张良培,王毅,李平湘.基于各向异性扩散的SAR图像斑点噪声滤波算法.电子学报,2006,34(12)：2250～2254
[180]黄倩,王岩飞,张冰尘,苗慧.一种新的各向异性扩散SAR相干斑抑制算法.电子学报,2006,34(9)：1553～1557
[181]Hye Suk Kim, Yeong Joo Cho. Anisotropic diffusion for preserving boundary-edge. Advanced Communication Tchnology(ICACT), the 12th International Coference on, 2010,2,pp:1693-1698
[182]Krissian K, Aja Fernandez S. Noise-driven anisotropic filtering of MRI. IEEE Transactions on Image Processing,2009,18(10):2265-2274
[183]聂玉峰.Lagrange插值和Hermite插值的内在统一理论.高等数学研究,2010, 13(1)：13～14
[184]杜英芳,孙海田,许贵桥Lagrange插值算子导数逼近的平均收敛速度.天津师范大学学报(自然科学版),2008,28(2)：54～56
[185]程海来Lagrange线性插值公式在微积分中的应用.高等数学研究,2009,12(6)：46～47
[186]盛中平,王晓辉,李冰玉.多点多重Lagrange型插值公式东北师大学报(自然科学版),2007,39(2)：136～137
[187]李信富,李小凡.分形插值与拉格朗日插值的比较研究.黑龙江大学自然科学学报,2008,25(3)：323～326
[188]郭伟,潘仲明,杜金榜,王跃科.基于Lagrange插值的非整数延时滤波器算法.国防科技大学学报,2009,31(1)：90～94
[189]陈桂强,王丽琴,李玉鉴.基于拉格朗日插值多项式的彩色图像分存方案.计算机测量与控制,2008,16(7)：1030-1032
[190]付瑶,王淑云,孙毅.一种Lagrange插值多项式的线性组合.吉林大学学报(理学版),2007,45(1)：29～34
[191]Hui Hu, Lian Fang. Interpolation and fitting algorithms for GPS satellite orbit. Remote Sensing and Geoscience for Agricultural Engineering, Proc of SPIE,2009, 7491, pp:749109-1-5
[192]Wen Thong Chang, Wen Jen Ho. Adaptive interpolator with context modeling in lifting scheme for lossless coding. In Visual Communications and Image Processing, Proc of SPIE,2000,4067,686-693
[193]龚奕刚,吴锡生.基于边缘信息的图像自适应插值算法.计算机应用与软件,2009,26(4)：225～239
[194]党向盈,吴锡生,赵勇.基于边缘最大梯度的多方向优化插值算法.计算机应用研究,2007,24(9)：317～320
[195]詹艳艳,徐荣聪,陈晓云.基于插值边缘算子的时间序列模式表示.模式识别与人工智能,2007,20(3)：421～527
[196]周春霞,吴锡生.基于方差和边缘插值的邻近点图像修复算法.计算机工程与应用,2008,44(14)：184～186
[197]张慧芯,屈小波,闫敬文.基于斜坡边缘模型的图像插值新算法.计算机工程,2009,35(10)：206～208
[198]孔凡树,艾东,贾超,姚芳,皱琪,王蓓蓓.基于学习边缘信息的图像插值算法.计算机工程与设计,2009,30(13)：3157～3159
[199]吴锡生,党向盈,赵勇.基于阈值控制的边缘自适应快速图像插值算法.计算机 工程,2007,33(22)：226～260
[200]李锌,张飞舟.基于再生核滤波器的边缘保护图像插值方法.计算机工程与应用,2008,44(13)：179～181
[201]刘艳琪,罗扬.一种新的基于图像边缘的插值算法.电脑知识与技术,2009,5(13)：3470～3471
[202]Ma J, Chan J C W, Canters F. Fully automatic subpixel image registration of multiangle CHRIS/Proba data, IEEE Transactions on Geoscience and Remote Sensing,2010, PP(99):1-11
[203]Xie Yurui, Xie Mingyuan, Yang Ling. A new non-rigid image registration algorithm using the finite-element method,2010 Second International Workshop on Education Technology and Computer Science(ETCS),2010,1:206-210
[204]Jae Hak Lee, Yong Sun Kim, Duhgoon Lee, Dong Goo Kang, Jong Beom Ra. Robust CCD and IR iamge registration using gradient-based statistical information, IEEE Signal Processing Letters,2010,17(4):347-350
[205]陈卫兵.几种图像相似度量的匹配性能比较.计算机应用,2010,30(1)：98～100
[206]高军,李学伟,张建,卢秉恒.基于模板匹配的图像配准算法.西安交通大学学报,2007,41(3)：307～311
[207]黄勇杰,王树国,张生.基于区域特征的图像自动配准方法.计算机工程与设计,2009,30(16)：3850-3855
[208]Vural M F, Yardimci Y, Temizel A. Rgistration of multispectral satellite images with orientation-restricted SIFT. Geoscience and Remote Sensing Symposium, IEEE International(IGARSS),2009,3, pp:Ⅲ-243-246
[209]Thomas Diego, Sugimoto Akihiro. Robust range image registration using local distribution of albedo, IEEE 12th Internatinal Conference on Computer Vision Workshops(ICCV),2009, pp:1654-1661
[210]Boyang Zhang, Ju Liu, Jinyu Chu, Jianping Qiao. A mutual information based sub-pixel registration method for image super resolution. Fifth Intrnational Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009, pp:422-425
[211]杨锣,郭宝龙,李雷达,杨占龙.基于图像几何特征点的仿射参数估计算法研究.计算机科学,2009,36(6)：279～281
[212]王嘉梅.基于MATLAB的数字信号处理与实践开发.西安：西安电子科技大学出版社,2007
[213]Hongyan Zhang, Liangpei Zhang, Huanfeng Shen, Pingxiang Li. A MAP approach for joint image registration, blur identification and superresolution, Fifth International Conference on Image and Graphics,2009, pp:97-102
[214]Aiye Shi, Huibin Wang, Chenrong Huang, Xuewu Zhang. An improved method for joint image registration and superresolution. International Conference on Test and Measurement(ICTM),2009,1, pp:383-386
[215]王静,章世平,孙权森,夏德深.基于MAP估计的遥感图像频域校正超分辨率算法2010,40(1)：84～88
[216]吴彦君,袁杰,王伟希,郑岩.基于视频模式识别的快速超分辨率重建.图像分析,2010,4,38～41
[217]杨欣,王从庆,费树岷.基于最大后验概率的SAR图像自适应超分辨率盲重建.宇航学报,2010,31(1)：217～221
[218]吴伟巍,曾庆山,刚铁金.基于遗传算法的超分辨率重建图像的重建.计算机工程与应用,2009,45(35)：199～201
[219]Ytku Senses E, Ulusoy Ⅰ. Blur estimation and superresolution from multiple registered images. IEEE 17th Signal Processing and Communications Applications Conference,2009, pp:660-663
[220]Nguyen M Q, Atkinson P M, Lewis H G. Superresolution mapping using a Hopfield neural netwok with fused images. IEEE Transactions on Geoscience and Remote Sensing,2006,44(3):736-749
[221]Tao Wang, Yan Zhang, Yongsheng Zhang, Lixia Lin. Automatic superresolution image reconstruction based on hybrid MAP-POCS. Internatinal Conference on Wavelet Analysis and Pattern Recognition(ICWAPR),2007,1, pp:426-431
[222]曹聚亮.图像超分辨率处理、成像及其相关技术研究.湖南：国防科技大学博士学位论文,2004
[223]乔建苹.超分辨率重建与图像增强技术研究.山东：山东大学博士学位论文,2008
[224]Schultz R R, Stevenson R L. Extraction of high-resolution frames from video sequences. IEEE Trans. On Image Processing,1996:5(6):996-1011
[225]娄帅,丁振良,袁峰,李晶.一种空间自适应正则化MAP超分辨率重建算法.计算机应用与软件,2009,26(12)：238～240
[226]肖创柏,禹晶,薛毅.一种基于MAP的超分辨率图像重建的快速算法.计算机研究与发展,2009,46(5)：872～880
[227]王素玉,沈兰荪,卓力,李晓光.一种基于权值矩阵的序列图像超分辨率盲复原算法.电子学报,2009,37(6)：1198～1202
[228]Ayers G R, Dainty J C. Iterative blind deconvolution method and its applications[J]. Optics Letters,1988,13(7):547-549
[2]屈惠明.红外成像电子学理论及其关键技术研究.南京：南京理工大学博士学位论文,2007
[3]蒋一明,王克勇,郑链,等.坦克目标的红外成像建模与仿真.红外技术,2008,30(1)：39-42
[4]KEITH L. Challenges in the evolution of advanced imaging systems. Proceedings of SPIE,2007,6714:1-7
[5]何伟,焦斌斌,薛惠琼,等.非冷红外焦平面阵列进展.电子工业专业设备,2008,37(5)：18～23
[6]张敬贤,李玉丹,金伟其.微光与红外成像技术.北京：北京理工大学出版社.1995
[7]金伟其,刘广容,白廷柱,王霞.夜视领域几个热点技术的进展及分析.光学技术,2005,31(3)：405～509
[8]简耀波.红外图像处理中的关键算法研究.武汉.华中科技大学博士学位论文,2009
[9]江照意.典型目标场景的红外成像仿真研究.杭州.浙江大学博士学位论文,2007
[10]孙恋君.微测辐射热计阵列性能及信号处理电路研究.南京.南京理工大学博士学位论文,2008
[11]邢素霞.非制冷红外热成像系统研究.南京.南京理工大学博士学位论文,2005
[12]王晓宇.红外图像分析关键技术研究.武汉.华中科技大学博士学位论文,2008
[13]常本康,蔡毅.红外成像阵列与系统.北京：科学出版社,2006
[14]Stuart Kleinfelder, Alison Hottes, Roger Fabian W. Pease. Focal plane array readout integrated circuit with per-pixel analog-to-digital and digital-to-analog conversion. Proceedings of SPIE,2000,4028:139-147
[15]Sang-Gu Kang, Doo H. Woo, Hee C. Lee. Infrared focal plane array readout integrated circuit with on-chip 14 b A/D converter. Proceedings of SPIE. 2004,5234:287-295
[16]Chih-Cheng Hsieh, Chung-Yu Wu. Focal-plane-arrays and CMOS Readout Techniques of Infrared Imaging Systems. IEEE Transactions on Circuits and Systems for Video Technology,1997,7(4):594-605
[17]Marion B. Reine. Review of HgCdTe photodiodes for IR detection. Proceedings of SPIE,2000,4028:320-330
[18]Philippe M. Tribolet, Patricia Costa, P. Fillon, et al. Large staring arrays at SOFRADIR. Proceedings of SPIE,2003,4820:418-428
[19]Sarath D. Gunapala, Sumith V. Bandara, John K. Liu. Recent developments and applications of quantum well infrared photodetector focal plane arrays, Proceedings of SPIE,2000,4028:262-275
[20]A. M. Filachev, V.P. Ponomarenko, I. I. Taubkin, M. B. Ushakova. Infrared focal plane arrays:state of the art and development trends. Proceedings of SPIE, 2003,5126:52-85
[21]K. Buskila, S. Towito, E. Shmuel, R. Levi, N. Kopeika, K. Krapels, R. G. Driggers, R.H. Vollmerhausen, C.E. Halford. Atmospheric modulation transfer function in the infrared. Appl Opt.,2004,43(2):471-482
[22]张毅,柏连发,陈钱,顾国华.红外焦平面微扫描空间分辨率性能分析与估算.红外与激光工程,2009,38(2)：221-225
[23]罗海波,史泽林.红外成像制导技术发展现状与展望.红外与激光工程,2009,38(4)：565～573
[24]王成刚,孙浩,李敬国,朱西安.双色碲镉汞红外焦平面探测器发展现状.激光与红外,2009,39(4)：367～371
[25]陈丽菊,刘巍.近红外光谱分析技术及发展前景.现代物理知识,2006,18(2)：10～11
[26]Richard Blackwell, Steven Geldart, Margaret Kohin, et al, Recent technology advancements and applications of advanced uncooled imagers, Proceedings of SPIE., 2004,5406:422-427
[27]蔡毅.对第三代热成像技术的思考,展望2010年中国夜视技术.中国兵工学会第四界夜视技术专业委员会主办,广西北海,2003.11
[28]吴诚,苏君红,潘顺臣,冯生荣,金伟其.对中波与长波红外焦平面热成像的一些探讨.红外技术.,2002,24(2)：6～8
[29]蔡毅,汤锦亚.对红外热成像技术发展的几点看法红外技术.2000,22(2)：2～6
[30]张天序,施长城,李洁珺,刘慧娜,袁雅婧,周泱.红外焦平面阵列非均匀性自适应校正算法研究进展.红外与毫米波学报,2007,26(6)：409～413
[31]石岩,张天序,李辉,曹治国.一种考虑红外焦平面器件非线性响应的非均匀校正方法.红外与毫米波学报,2004,23(4)：251～256
[32]屈惠明,陈钱.红外焦平面阵列二元非线性的非均匀性理论模型.电子学报, 2008,36(11)：2150～2153
[33]白俊奇,陈钱,钱惟贤,屈惠明,王娴雅,左超.基于环境温度的红外焦平面阵列非均匀性校正.红外与毫米波学报,2010,29(1)49～52
[34]Hardie R C, Hayat M M, Amstong E. Scene-based nonuniformity correction using video sequences and registration. Applied Optics,2000,39(8):1241-1250
[35]Ratliff B M, Hayat M M, Tyo H S, Generalized algebraic scene-based nonuniformity correction algorithm. Journal of the Optical Society of America A,2005,22:239-249
[36]Narendra P M, Foss N A. Shutterless fixed pattern noise correction for infrared imaging arrays. Proceedings of SPIE,1981,282:44-51
[37]Scribner D A, Sakady K A, Caufield J T. Nonuniformity correction for staring IR focal Plane arrays using scene-based techniques, Infrared Detectors and Focal Plane Arrays, SPIE,1990,1308:224-233
[38]Scribner D A, Sakady K A, Kruer M R. Adaptive retina-like preprocessing for imaging detector arrays. Proc. IEEE,1993:1955-1960
[39]Harris H G, Chiang Y M. Nonuniformity correction using the constant-statistics constraint analog and digital implementations. Proceedings of SPIE,1997, 3061:895-905
[40]Harris H G, Chiang Y M. Minizing the ghosting artifact in scene-based nonunifomity correction. Proceedings of SPIE,1998,3377:106-113
[41]赖睿,杨银堂.场景自适应的红外焦平面阵列非均匀性校正新方法.西安电子科技大学学报,2009,36(2)：228～232
[42]Weixian Qian, Qian Chen, Guo hua Gu. Space low-pass and temporal high-pass nonuniformity correction algorithm. Optical Review,2010,17(1):24-29
[43]Hayat M M, Torres S N, Amstrong, Stephen C Cain, Brian Yasuda. Statistical algorithm for nonuniformity correction in focal-plane arrays. Applied Optics,1999, 38(8):772-780
[44]Torres S N, Pezoa J E, Hayat M M. Scene-based nonuniformity correction for focal plane arrays by the method of the inverse covariance form. Applied Optics, 2003,42(29):5872-5881
[45]Torres S N, Hayat M M. Kalman filtering for adaptive nonuniformity correction in infrared focal-plane arrays. Journal of the Optical Society of America A, 2003,20:470-480
[46]Pezoa J E, Hayat M M, Torres S N, Multimodel kalman filtering for adaptive nonuniformity correction in infrared sensors. Journal of the Optical Society of America A,2006,23:1282-1291
[47]Jorge E Pezoa,Majeed M Hayat, Sergio N Torres, Md Saifur Rahman. Multimodel Kalman filtering for adaptive nonuniformity correction in infrared sensors. J. Opt. Soc. Am.A.2006,23(6):1282-1291
[48]周慧鑫,魏亚姣,秦翰林,王炳健.基于非线性模型的卡尔曼滤波非均匀性校正算法.光学学报,2009,29(2)378～381
[49]张天序,石岩,曹治国.红外焦平面非均匀性噪声的空间频率特性及空间自适应非均匀性校正方法.改进红外与毫米波学报,2005,24(4)：255～260
[50]Shehadeh M, Kuybeda O. Robust nonuniformity correction in infrared images based on global motion. IEEE 25th Convention of Electrical and Electronics Engineers in Israel,2008:275-279
[51]Pipa D, da Silva E, Pagliari C, Perez M M. Joint bias and gain nonuniformity correction of infrared videos using tensorial-RLS technique.200916th IEEE International Conference on Image Processing (ICIP),2009:3897-3900
[52]Cohen M, Cauwenberghs GFloating-gate adaptation for focal-plane online nonuniformity correction. IEEE Transactions on Circuits and Systems II:Analog and Digital Signal Processing,2001:83-89
[53]Weixian Qian, Qian Chen, Guohua Gu, Zhiqiang Guan. Correction method for stripe nonuniformity. Applied Optics,2010,49(10):1764-1773
[54]吴新社,蔡毅.红外凝视成像系统中的光学微扫描技术.红外与毫米波学报,2007,26(1)：10～14
[55]吴新社,范乃华,李龙,徐世春,蔡毅.铁电型非制冷红外焦平面探测器的调制器设计,红外技术,2007,29(6)：333～336
[56]吴新社,蔡毅,范乃华,李龙.铁电型非制冷红外焦平面探测器的斩波器设计.红外与激光工程,2006,增刊
[57]K. Awamoto, U. Ito, H. Ishizaki. Resolution improvement for HgCdTe IRCCD. Infared Detectors and Focal Plane Arrays II, SPIE,1992,1689
[58]J. Fortin, P. Chevertte. Realization of a fast microscannning device for infrared focal plane arrays. SPIE,2743,185
[59]R. K. McEwen, P. A. Mannig. European Uncooled thermal imaging technology. BAE SYSTEMD Infared Limited, March 2000
[60]W. Cabanski, R. Breiter, K. H. Mauk. Miniaturized high performance starring thermal imaging system. SPIE,2000,4028
[61]沈卫.法国泰勒斯公司推出新型武器热瞄具.轻兵器,2005
[62]H. S. Kim, C. W. Kim, S. M. Hong. Compact mid-wavelength infrared zoom camera with 20:1 zoom range and automatic athermalization. Optical Engineering,2002 41(7):1661-1667
[63]Alain Bergeron, Loic Le Noc, Bruno Tremblay, Francois Lagace, Luc Mercier, Francois Duchesne, Linda Marchese, Julie Lambert, Michel Hacob, Martin Morissette, Hubert Jerominek. Flexible 640×480 pixel infrared camera module for fast prototyping. Proceedings of SPIE,2009,7481:74810L-1-74810L-9
[64]首山雄,陈进勇.微扫描多帧平滑FPN提高CMOS图像传感器信噪比.浙江大学学报,2002,36(6)：621～623
[65]金伟其,王春勇,张楠,王岭雪,卢萍.扫描型焦平面热成像系统的亚像元处理算法研究.红外与毫米波学报,2005,24(4)：261-264
[66]张楠,金伟其,苏秉华,刘扬阳.高分辨力红外热图像重建算法的进展及研究.兵工学报,2005,26(2)：173～176
[67]Eric Kaltenbacher, Russell C. Hardie. High resolution infrared image reconstruction using multiple, low resolution, aliased frames. SPIE,2751, pp:142-152
[68]Stone H S, Orchard M T, Ee-Chien Chang and Martucci S A. A fast direct Fourier-based algorithm for subpixel registration of images. IEEE Transactions on Geoscience and Remote Sensing,2001,39(10):2235-2243
[69]Hassan Foroosh (Shekarforoush), Josiane B Zerubia, Senior Member, IEEE, and Marc Berthod. Extension of phase correction to subpixel registration. IEEE,2002, pp:188-200
[70]Eun Sil Lee and Moon Gi Kang. Regularized adaptive high-resolution image reconstruction considering inaccurate subpixel registration. IEEE Transactions on Image Processing,2003,12(7):826-837
[71]徐超,金伟其,李雅琼,王霞.一种改进的凝视焦平面探测器亚像元成像处理算法.电子学报,2007,35(8)：1608～1611
[72]Manuel Guizar-Sicairos, Samuel T Thurman, and James R Fienup. Efficient subpixel image registration algorithms. Optics Letters,2008,33(2):156-158
[73]金伟其,陈翼男,王霞,李雅琼,王岭雪.考虑探测器填充率及微扫描对位偏差的扫描型亚像元热成像算法.红外与毫米波学报,2008,27(4)：308～312
[74]高美静,金伟其,王霞,于杰.光学微扫描显微热成像扫描零点定标方法研究.光学学报,2009,29(8)：2175～2179
[75]韩玉兵.图像及视频序列的超分辨率重建.南京：东南大学博士学位论文,2005
[76]何宇清.图像超分辨率重建关键技术研究.天津：天津大学博士学位论文,2007
[77]陈艳.图像超分辨率重建关键技术的研究.上海：上海交通大学博士学位论文,2007
[78]丁海勇.遥感图像超分辨率重建技术研究.徐州：中国矿业大学博士学位论文,2008
[79]宋锐.视频和图像序列的超分辨率重建技术研究.西安西安电子科技大学博士学位论文,2009
[80]H. A Brown. Effect of truncation on image enhancement by prolate spheroidal function. Journal of the Optical Society of America A,1969,59:228-229
[81]B. R. Hunt, P. Sementill. Description of a poisson imagery super-resolution algorithm, Astronomical Data Analysis Software and System. Astronomical Society of the Pacific, San Framcisco,1992
[82]C. K. Rusforth. In image reconstruction, theory and application. Academic Press, New York,1987
[83]Kim S P, Bose N K, Valenzuela H M. Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Transactions on Acoustics, Speech, and Signal Processing,1990,38(6):1013-1027
[84]Kim S P, Su W. Recursive high-resolution reconstruction of blurred multiframe images. In Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing, Toronto Canada, May 1991,4:2977-2980
[85]Bose N K, Kim H C, Valenzuela H M. Recursive total least squares algorithm for image reconstruction from noisy, undersampled multiframes. Multidimensional Systems and Signal Processing,1993,4(3):253-268
[86]Tekalo A M, Ozekan M K, Sezan M I. High-resolution image reconstruction from lower-resolution image sequences and space-varying image restoration. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, San Francisco CA,1992,111:169-172
[87]Keren D, Peleg S, Brada R. Image sequence enhancement using subpixel displacements. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 1988:742-746
[88]Schuler J M, Howard J G, Warren P R, etc. Resolution enhancement through TARID processing. In Proceedings of SPIE-the International Society for Optical Engineering, San Jose, CA, United states,2002, pp872-876
[89]Schuler J M, Howard J G, Warren P R, etc. TARID-based image superresolution. in Proceedings of SPIE-the International Society for Optical Engineering, Orlando, Fl, United states,2002, pp247-254
[90]Aizawa K, Komatsu T, Saito T. A scheme for acquiring very high resolution images using multiple camers. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Proceedings, San Francisco, CA Mar.1992,3:289-292
[91]Shmuel P, Danny K, Limor S. Improving image resolution using subpixel moton. Pattern Recognition Letter,1987,5(3):223-226
[92]Irani M, Peleg S. Super resolution from image sequences. In Proceeding of the 10th International Conference on Pattern Recognition, Atlantic City, NJ, June 1990, 2:115-120
[93]Irani M, Peleg S. Improving resolution by image registration. CVGIP:Graphical Models and Image Processing,1991,53(3):231-239
[94]Mann S, Pickard R W. Virtual Bellows:Construting high quality stills from video. In Proceedings of the IEEE international Conference on Image Processing, Austin, TX, 1994,363-367
[95]Tom B C, Katsaggelos A K. Multi-channel image identification and restoration using the expectation maximization algorithm. In Applications of Digital Image Processing XVII, San Diego, CA, July 1994, vol.2298 of Proceedings of theSPIE,316-331
[96]Tom B C, Katsaggelos A K. Reconstruction of a high-resolution image by simultaneous registration, restoration and interpolation of low-resolution images. In Proceedings of the IEEE International Conference Image Processing, Washington DC,1995, 2:539-542
[97]Tom B C, Katsaggelos A K, Galatsanos N P. Reconstruction of a high resolution image from registration and restoration of low resolution images. In Proceedings of the IEEE International Conference Image Processing, Austin, TX,1994,Ⅲ:553-557
[98]Tom B C, Katsaggelos A K. A iterative algorithm for improving the resolution of video sequences. In Visual Communications and Image Processing of Proceedings of the SPIE,1996,2727,1430-1438
[99]Schultz R R, Stevenson R L. Extraction of high-resolution frames from video sequences. Image Processing, IEEE Transactions on,1996,5(6):996-1011
[100]Hardie R C, Barnard K J, Armstrong E E. Joint MAP registration and high-resolution image estimation using a sequence of Undersampled images. IEEE Trans. On Image Processing,1997,6(12):1621-1633
[101]Cheeseman P, Kanefsky B, Kraft R, etc. Super-resolved surface reconstruction from multiple images[DB/OL]. http://hanson.gmu.edu/image.pdf,1994
[102]Elad M, Feuer A. Restoration of a single superresolution image from several blurred, noisy and undersampled measured images. IEEE Transactions on Image Processing, 1997,6(12):1646-1658
[103]Elad M, Feuer A. Super-resolution reconstruction of image sequences. IEEE Transactions on Pattern Analysis and Machine Intelligence,1999,21(9):817-834
[104]Sementilli P J, Nadar M S, Hunt B R. Empirical evaluation of a bound on image superresolution performance. Proceedings of SPIE-the International Society for Optical Engineering,1994,2302:178-187
[105]Lorette A, Shekarforoush H, Zerubia J. Super-resolution with adaptive regularization. In IEEE International Coference on Image Processing, Los Alamitos, CA, USA, 1997:169-172
[106]Farsiu S, Robinson M D, Elad M etc, Fast and robust multiframe super resolution. IEEE Transactions on Image Processing, Oct,2004,13(10):1327-1344
[107]Stark H, Oskoui P. High-resolution image recovery from image-plane arrays, using convex projections. Journal of the Optical Society of America A,1989, 6(11):1715-1726
[108]Patti A J, Altunbasak Y. Artifact reduction for set theoretic super resolution image reconstruction with edge adaptive constraints and higher-order interpolants. IEEE Transactions on Image Processing,2001,10(1):179-186
[109]Patti A J, Sezan M I, Tekalp A M. Robust methods for high-quality still from interlaced video in the presence of dominant motion. IEEE Transactions on Circuits and Systems for Video Technology,1997,7(2):328-342
[110]Eren P E, Sezan M I, Tekalp A M. Robust object-based high-resolution image reconstruction from low-resolution video. IEEE Transactions on Image Processing, 1997,6(10):1446-1451
[111]Russell C. Hardie, Kenneth J. Barnard, John G. Bognar, Ernest E. Armstrong, Edward A. Watson. High resolution image reconstruction from a sequence of rotated and translated frames and its application to an infrared imaging system. Optical Engineering,1997, pp1-27
[112]Mohammad S. Alam, John G. Bognar, Russell C. Hardie, Brian J. Yasuda. Infared image registration and high-resolution reconstruction using multiple translationally shifted aliased video frames. IEEE Transactions on Instrumentation and Measurement,2000,49(5):915-923
[113]Russell C. Hardie, Douglas R. Droege. A map estimator for simultaneous superresolution and detector nonunifomity correction. EURASIP Journal on Advances inSignal Processing,2007, ID89354, ppl-11
[114]Wenyi Zhao, Chao Zhang. Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion. Journal of the Optical Society of America A, 2008,25(7):1668-1681
[115]Tuan Q. Pham, Lucas J. Van Vliet, Klamer Schutte, Robust super-resolution by minimizing a Gaussian-weighted L2 Error Norm.4th AIP International Conference and the 1st Congress of the IPIA, Journal of Physics.:Conference Series124(2008)012037,pp1-20
[116]Irene G. Karybali, Emmanouil Z. Psarakis, Kostas Berberidis, Georgios D. Evangelidis. An efficient spatial domain technique for subpixel image registration. Signal Processing:Image Communication,2008,23:711-724
[117]张晓飞,基于DSP的红外焦平面阵列非均匀性校正技术研究.重庆：重庆大学,2002
[118]陈永甫.红外辐射红外器件与典型应用.北京：电子工业出版社,2004
[119]王义玉.红外探测器.北京：兵器工业出版社,1993
[120]Jan Baars. Max Schulz. Performance characteristics, measurement procedures and figures of merit for infrared focal plane arrays. Proceedings of SPIE. 1995(2470):141-155
[121]W. A. Cabanski and M. J. Schulz. Electronic and optical properties of silicide/silicon ir detectors. Proceedings of SPIE.1991(1484):81-97
[122]陈西曲.非致冷红外焦平面的读出电路及测试系统研究.武汉华中科技大学博士学位论文,2007
[123]Hsieh C C, Wu C Y, Jih F W. Focal-plane-arrays and CMOS readout techniques of infrared imaging systems. IEEE Trans. On CSVT,1997,7:594-605
[124]Zhao Y, Mao M Y, Horowitz R. Optomechanical uncooled infared imaging systems:Design, microfabrication and performance. J. Microelectromechanical Sys, 2002,11:136-146
[125]米本和也(著),陈榕庭,彭美桂(译)CCD/CMOS图像传感器基础与应用.北京：科学出版社,2005
[126]隋修宝,陈钱,顾国华.环境温度对红外图像非均匀性影响的研究.光子学报,2008,37(12)：2572～2575
[127]Pipa D, Da Silva E, Pagliari C, Perez M M. Joint bias and gain nonuniformity correction of infrared videos using tensorial-RLS technique. Image Processing(ICIP), 16th IEEE International Conference,2009, pp:3897-3900
[128]Shehadeh M, Kuybeda O. Robust nonuniformity correction in infrared images based on global motion. Electrical and Electronics Engineers in Israel, IEEE 25th Convention of,2008, pp:275-279
[129]Huixin Zhou, Hanlin Qin, Rui Lai, Shangqian Liu. Adaptive filtering for nonuniformity correction in infrared focal plane arrays. Infrared and Millimeter Waves 15th International Conference on Terahertz Electronics. IRMMWTHZ Joint 32nd International Conference on,2007, pp:510-511
[130]Yongjin Liu, Hong Zhu, Yigong Zhao. New scene-based nonuniformity correction algorithm of infrared focal plane arrays. Image and Signal Processing and Analysis, ISPA 2007 5th International Symposium on,2007, pp:274-277
[131]Grzegorz Bieszczad, Tomasz Sosnowski, Henryk Madura, Mariusz Kastek, Jaroslaw Barela. Adaptable infrared image processing module implemented in FPGA. Infrared Technology and Applications ⅩⅩⅩⅥ, Proc. of SPIE,2010,7660,pp:76603Z-1-10
[132]Jonah C McBride, Magnus S Snorrason. Improving scene-based non-uniformity correction for infrared images using frequency domain processing. Thermosense ⅩⅩⅩⅠ, Proc. of SPIE,2009,7299,pp:729903-1-11
[133]Liquan Dong, Xiaohua Liu, Yuejin Zhao, Mei Hui, Xiaoxiao Zhou. Scene-based nonuniformity correction algorithm for MEMS-based un-cooled IR image system. Infrared Systems and Photoelectronic Technology Ⅳ, Proc. of SPIE,2009,7419, pp74190Y-1-12
[134]Daniel Pipa, Eduardo A B, Carla Pagliari, Marcelo M Perez. Joint bias and gain nonuniformity correction of infrared videos using tensorial-rls technique. ICIP2009. IEEE,2009, pp:3897-3900
[135]Gyong Jin Oh, Lyang June Kim, Sue Ho Sheen, Gyou Phyo Koo, Sang Hun Jin, Bo Yeon Yeo, Jone Ho Lee. Implementation of real time nonuniformity correction with multiple NUC tables using FPGA in an uncooled imaging system. Infrared Technology and Applications ⅩⅩⅩⅤ, Proc. of SPIE,2009,7298,pp:72982E-1-8
[136]Zhenguo Liu, Xiaomei Hu, Jin Lu. An improved neural network non-uniformity correction for IRFPA. International Symposium on Photoelectronic Detection and Imaging, SPIE,2009,7383:pp:738330-1-8
[137]Douglas R Droege. Scene-based nonuniformity correction using texture-based adaptive filtering. Infrared Technology and Applications ⅩⅩⅩⅢ, Proc. of SPIE, 2007,6542, pp:65423R-1-12
[138]Sebastian E Godoy, Sergio N Torres, Jorge E Pezoa, Majeed M Hayat, Qi Wang. Nonuniformity correction algorithm based on a noise-cancellation system for infrared focal-plane arrays. Infrared Technology and Applications ⅩⅩⅩⅢ, Proc. of SPIE,2007,6542, pp:65423S-1-11
[139]徐田华,赵亦工.基于场景的红外焦平面非均匀校正技术研究.红外与毫米波学报,2004,23(4)：257～261
[140]Scribner D, Sarkady K, Kruer M. Adaptive nonuniformity correction for infared focal plane arrays using neural network. Proc of Infared Sensors:Detectors, Electronics, and Signal Processing:1541. San Diego:SPIE,1991:100-109
[141]董立泉,金伟其,隋婧.基于场景的红外焦平面阵列非均匀性校正算法综述.光学技术,2008,34(suppl.)：112-122
[142]孙恋君,张俊举,王世允,常本康,钱芸生.非制冷微测辐射热计探测器工作温度特性研究.红外与毫米波学报,2007.26(3)：232～236
[143]Balaji Narayanan. Nonuniformity correction for focal plane arrays and partition based superresolution of video with application to an infared imaging system. Dayton, the Doctor Dissertation of University of Dayton,2005
[144]刘永进,朱红,赵亦工.基于红外焦平面阵列读出结构的非均匀性校正算法.光学精密工程,2008,16(1)：128～133
[145]黄倩,王岩飞,张冰尘,苗慧.一种新的各向异性扩散SAR相干斑抑制算法.电子学报,2006,34(9)：1553-1557
[146]Lai Rui, Yang Yin Tang, Zhou Duan, Li Yue Jin. Improved neural network based scene-adaptive nonuniformity correction method for infrared focal plane arrays. Applied Optics,47(24):4331-4335
[147]J Kim, C W, Lee, J K Lee, J S Hwang, J H Park. Comparsion of adaptive systems for noise reduction in speech performance. In Proceeding of the IEEE 38th Southeastern Symposium on System Theory,2006,pp:123-127
[148]D G Manoakis, V K Ingle, S M Kogon. Statistical and adaptive signal processing(McGraw-Hill,2000).
[149]John G Harris, Yu-Ming Chiang. Nonuniformity correction of infrared image sequences using the constant-statistics constraint. IEEE Transactions on Image Processing,1999,8(8):1148-1151
[150]Esteban Vera R, Sergio Torres I. Ghosting reduction in adaptive nonuniformity correction of infared focal-plane array image sequences. IEEE,2003,111001-1004
[151]Narendra P M, Foss N A. Shutterless fixed pattern noise correction for infared imaging array. SPIE,1981,282:44-51
[152]John G Harris, Yu-Ming Chiang. Minimizing the "ghosting" artifact in scene-based nonuniformity correction. Part of the SPIE Conference on Infrared Imaging Systems: Design, Analysis, Modeling and Testing IX, Orlando,1998,3377:106-113
[153]Zhang Tianxu, Shi Yan. Edge-directed adaptive nonuniformity correction for staring infrared focal plane arrays. Optical Engineering,2006,45(1):1-11
[154]张天序,石岩.红外焦平面阵列非均匀性自适应校正算法中目标退化与伪像的消除方法.红外与毫米波学报,2005,24(5)：335～340
[155]刘会通,马红伟.自适应非均匀性校正中“鬼影”问题的分析.红外技术,2003,25(5)：30～32
[156]徐雨明,文双春.数字图像插值算法的分析与实现.福建电脑,2007,1：90～91
[157]刘洪臣,冯勇,杨旭强.基于双三次B样条曲面亚像元图像插值方法.哈尔滨工业大学学报,2007,39(7)：1121～1124
[158]江铭炎,李兴江,袁东风.2*图像插值放大处理的方法.山东大学学报(理学版),2003,38(3)：79～81
[159]符祥,郭宝龙.图像插值技术综述.计算机工程与设计,2009,30(1)：141～144
[160]Edward A Watson, Robert A Muse, Fred p Blommel. Aliasing and blurring in microscanned imagery. Infrared Imaging Systems, SPIE,1992,1689,pp:242-250
[161]S P Kim, N k Bose, H M Valenzuela, Recursive reconstruction of high resolution image from noisy undersampled multiframes. IEEE Trans. Acoust. Speech Signal Process.1990,38(6):1013-1027
[162]Joseph C Gillette, Thomas M Stadtmiller. Aliasing reduction in staring infrared imagers utilizing subpixel techniques. Optical Engineering,1995,34(11):3130-3137
[163]隋修宝.非制冷凝视热像仪成像理论以及关键技术研究.南京：南京理工大学博士学位论文,2009
[164]李兰兰.基于偏微分方程的图像复原和增强算法研究.南京：东南大学博士学位论文,2004
[165]Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans. On PAMI,1990,12(7):629-639
[166]Gilboa G, Sochen N, Zeevi Y Y. Image enhancement and dinoising by complex diffusion processing. IEEE Trans. On PAMI,2004,26(8):1020-1036
[167]严家斌,刘贵忠.一种新的各向异性扩散时间尺度估计方法.计算机工程,2008,34(2)：43～45
[168]Weeratunga S, Kamath C. Comparison of PDE-based non-linear anistropic diffusion techniques for image denoising. Proc of SPIE,2003,5014:201-212
[169]Shih A C, Liao H M, Lu C S. A new iterated two-band diffusion equationtheory and its application. IEEE Transaction on Image Processing,2003,12(4):466-476
[170]H Bruder, R Raupach, E Klotz, K Stierstorfer, T Flohr. Spatio-temporal filtration of dynamic CT data using diffusion filters. Physics of Medical Imaging, Proc of SPIE, 2009,7258,pp:725857-1-10
[171]Hongmin Zhang, Xiaohua Lv. Modified robust anisotropic diffusion denoising technique with regularized Richardson-lucy deconvolution fro two-photon microscopic images. Optical Engineering,2008,47(4):047004-1-8
[172]Jinshan Tang, Qingling Sun. A 3-D anisotropic diffusion filter for speckle reduction in 3-D ultrasound images. Three-Dimensional Imaging Metrology, SPIE,2009, 7239,pp:72390T-1-9
[173]Zhentian Wang, Li Zhang, Yuxiang Xing, Ziran Zhao. PDE regularization for Bayesian reconstruction of emission tomography. Physics of Medical Imaging, Proc. of SPIE,2008,6913,pp:69132X-1-8
[174]Eric J Wharton, Karen A Panetta, Sos S Agaian. Edge preserving image enhancement using anisotropic diffusion. Image Processing:Algorithms and Systems VI, SPIE, 2008,6812,pp:681218-1-10
[175]张相芬,DTI图像去噪方法研究.上海：上海交通大学博士学位论文,2008
[176]王毅,张良培,李平湘.各向异性扩散平滑滤波的改进算法.中国图象图形学报,2006,11(2)：210～216
[177]Catte F, Lions P L, Morel J. Image Selective smoothing and edge detection by nonlinear diffusion. SIAM Journal on Numerical Analysis,1992,29(3):845-866
[178]孙兆林MATLAB 6.X图像处理.北京清华大学出版社,2002
[179]张良培,王毅,李平湘.基于各向异性扩散的SAR图像斑点噪声滤波算法.电子学报,2006,34(12)：2250～2254
[180]黄倩,王岩飞,张冰尘,苗慧.一种新的各向异性扩散SAR相干斑抑制算法.电子学报,2006,34(9)：1553～1557
[181]Hye Suk Kim, Yeong Joo Cho. Anisotropic diffusion for preserving boundary-edge. Advanced Communication Tchnology(ICACT), the 12th International Coference on, 2010,2,pp:1693-1698
[182]Krissian K, Aja Fernandez S. Noise-driven anisotropic filtering of MRI. IEEE Transactions on Image Processing,2009,18(10):2265-2274
[183]聂玉峰.Lagrange插值和Hermite插值的内在统一理论.高等数学研究,2010, 13(1)：13～14
[184]杜英芳,孙海田,许贵桥Lagrange插值算子导数逼近的平均收敛速度.天津师范大学学报(自然科学版),2008,28(2)：54～56
[185]程海来Lagrange线性插值公式在微积分中的应用.高等数学研究,2009,12(6)：46～47
[186]盛中平,王晓辉,李冰玉.多点多重Lagrange型插值公式东北师大学报(自然科学版),2007,39(2)：136～137
[187]李信富,李小凡.分形插值与拉格朗日插值的比较研究.黑龙江大学自然科学学报,2008,25(3)：323～326
[188]郭伟,潘仲明,杜金榜,王跃科.基于Lagrange插值的非整数延时滤波器算法.国防科技大学学报,2009,31(1)：90～94
[189]陈桂强,王丽琴,李玉鉴.基于拉格朗日插值多项式的彩色图像分存方案.计算机测量与控制,2008,16(7)：1030-1032
[190]付瑶,王淑云,孙毅.一种Lagrange插值多项式的线性组合.吉林大学学报(理学版),2007,45(1)：29～34
[191]Hui Hu, Lian Fang. Interpolation and fitting algorithms for GPS satellite orbit. Remote Sensing and Geoscience for Agricultural Engineering, Proc of SPIE,2009, 7491, pp:749109-1-5
[192]Wen Thong Chang, Wen Jen Ho. Adaptive interpolator with context modeling in lifting scheme for lossless coding. In Visual Communications and Image Processing, Proc of SPIE,2000,4067,686-693
[193]龚奕刚,吴锡生.基于边缘信息的图像自适应插值算法.计算机应用与软件,2009,26(4)：225～239
[194]党向盈,吴锡生,赵勇.基于边缘最大梯度的多方向优化插值算法.计算机应用研究,2007,24(9)：317～320
[195]詹艳艳,徐荣聪,陈晓云.基于插值边缘算子的时间序列模式表示.模式识别与人工智能,2007,20(3)：421～527
[196]周春霞,吴锡生.基于方差和边缘插值的邻近点图像修复算法.计算机工程与应用,2008,44(14)：184～186
[197]张慧芯,屈小波,闫敬文.基于斜坡边缘模型的图像插值新算法.计算机工程,2009,35(10)：206～208
[198]孔凡树,艾东,贾超,姚芳,皱琪,王蓓蓓.基于学习边缘信息的图像插值算法.计算机工程与设计,2009,30(13)：3157～3159
[199]吴锡生,党向盈,赵勇.基于阈值控制的边缘自适应快速图像插值算法.计算机 工程,2007,33(22)：226～260
[200]李锌,张飞舟.基于再生核滤波器的边缘保护图像插值方法.计算机工程与应用,2008,44(13)：179～181
[201]刘艳琪,罗扬.一种新的基于图像边缘的插值算法.电脑知识与技术,2009,5(13)：3470～3471
[202]Ma J, Chan J C W, Canters F. Fully automatic subpixel image registration of multiangle CHRIS/Proba data, IEEE Transactions on Geoscience and Remote Sensing,2010, PP(99):1-11
[203]Xie Yurui, Xie Mingyuan, Yang Ling. A new non-rigid image registration algorithm using the finite-element method,2010 Second International Workshop on Education Technology and Computer Science(ETCS),2010,1:206-210
[204]Jae Hak Lee, Yong Sun Kim, Duhgoon Lee, Dong Goo Kang, Jong Beom Ra. Robust CCD and IR iamge registration using gradient-based statistical information, IEEE Signal Processing Letters,2010,17(4):347-350
[205]陈卫兵.几种图像相似度量的匹配性能比较.计算机应用,2010,30(1)：98～100
[206]高军,李学伟,张建,卢秉恒.基于模板匹配的图像配准算法.西安交通大学学报,2007,41(3)：307～311
[207]黄勇杰,王树国,张生.基于区域特征的图像自动配准方法.计算机工程与设计,2009,30(16)：3850-3855
[208]Vural M F, Yardimci Y, Temizel A. Rgistration of multispectral satellite images with orientation-restricted SIFT. Geoscience and Remote Sensing Symposium, IEEE International(IGARSS),2009,3, pp:Ⅲ-243-246
[209]Thomas Diego, Sugimoto Akihiro. Robust range image registration using local distribution of albedo, IEEE 12th Internatinal Conference on Computer Vision Workshops(ICCV),2009, pp:1654-1661
[210]Boyang Zhang, Ju Liu, Jinyu Chu, Jianping Qiao. A mutual information based sub-pixel registration method for image super resolution. Fifth Intrnational Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2009, pp:422-425
[211]杨锣,郭宝龙,李雷达,杨占龙.基于图像几何特征点的仿射参数估计算法研究.计算机科学,2009,36(6)：279～281
[212]王嘉梅.基于MATLAB的数字信号处理与实践开发.西安：西安电子科技大学出版社,2007
[213]Hongyan Zhang, Liangpei Zhang, Huanfeng Shen, Pingxiang Li. A MAP approach for joint image registration, blur identification and superresolution, Fifth International Conference on Image and Graphics,2009, pp:97-102
[214]Aiye Shi, Huibin Wang, Chenrong Huang, Xuewu Zhang. An improved method for joint image registration and superresolution. International Conference on Test and Measurement(ICTM),2009,1, pp:383-386
[215]王静,章世平,孙权森,夏德深.基于MAP估计的遥感图像频域校正超分辨率算法2010,40(1)：84～88
[216]吴彦君,袁杰,王伟希,郑岩.基于视频模式识别的快速超分辨率重建.图像分析,2010,4,38～41
[217]杨欣,王从庆,费树岷.基于最大后验概率的SAR图像自适应超分辨率盲重建.宇航学报,2010,31(1)：217～221
[218]吴伟巍,曾庆山,刚铁金.基于遗传算法的超分辨率重建图像的重建.计算机工程与应用,2009,45(35)：199～201
[219]Ytku Senses E, Ulusoy Ⅰ. Blur estimation and superresolution from multiple registered images. IEEE 17th Signal Processing and Communications Applications Conference,2009, pp:660-663
[220]Nguyen M Q, Atkinson P M, Lewis H G. Superresolution mapping using a Hopfield neural netwok with fused images. IEEE Transactions on Geoscience and Remote Sensing,2006,44(3):736-749
[221]Tao Wang, Yan Zhang, Yongsheng Zhang, Lixia Lin. Automatic superresolution image reconstruction based on hybrid MAP-POCS. Internatinal Conference on Wavelet Analysis and Pattern Recognition(ICWAPR),2007,1, pp:426-431
[222]曹聚亮.图像超分辨率处理、成像及其相关技术研究.湖南：国防科技大学博士学位论文,2004
[223]乔建苹.超分辨率重建与图像增强技术研究.山东：山东大学博士学位论文,2008
[224]Schultz R R, Stevenson R L. Extraction of high-resolution frames from video sequences. IEEE Trans. On Image Processing,1996:5(6):996-1011
[225]娄帅,丁振良,袁峰,李晶.一种空间自适应正则化MAP超分辨率重建算法.计算机应用与软件,2009,26(12)：238～240
[226]肖创柏,禹晶,薛毅.一种基于MAP的超分辨率图像重建的快速算法.计算机研究与发展,2009,46(5)：872～880
[227]王素玉,沈兰荪,卓力,李晓光.一种基于权值矩阵的序列图像超分辨率盲复原算法.电子学报,2009,37(6)：1198～1202
[228]Ayers G R, Dainty J C. Iterative blind deconvolution method and its applications[J]. Optics Letters,1988,13(7):547-549