遥感图像去云方法的研究及其应用
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摘要
随着光学图像增强方法研究的不断深入,特别是遥感数据的应用日益广泛,对制约遥感图像质量的重要因素—云的研究显得越来越重要。由于存在云噪声,大多数遥感数据不能获得应有的信息,因此在遥感图像中获取地物的信息,必须研究去云的方法。常用的去云方法有多光谱图像法、多幅图像插值法、多源数据融合法、同态滤波法以及采用对云不敏感的传感器方法等等,在一定的条件,对灰度图像较为有效。对于无先验知识的单幅有云噪声的遥感图像,则需要具体问题作具体分析。
对光学图像去云方法的研究,首先建立了云噪声影像模型,分析了遥感图像中云的特征,基于波的传播原理,提出了用惠更斯次波法提取遥感图像中云区和云影区,采用边缘模糊的方法,增强所提取区域的信息,进而实现遥感图像局部去云和去云影:基于云区渐变的特性,提出了用高次多项式曲线变换法,拉伸云区像素的灰度值,突出了云区图像的信息。
其次基于邻域法分析了同态滤波法的本质,就是在图像中滤去低频信号,正因为云在遥感图像中正好属于低频信息,故同态滤波法也能用于遥感图像去云。深入研究了E.Land在20世纪60年代提出的Retinex思想,以及无数学者在Land的基础上研究获得的各种各样算法,特别研究了工作在NASA和CWM的D.J.Jobson,Zia-ur Rahman,G.A.Woodell(简称JRW)等人的Retinex思想。揭示了Retinex算法的物理本质,提出了改进型多尺度Retinex算法:运用多尺度Retinex算法增强彩色图像后,在其亮度平均值附近以k倍标准差截取,再进行拉伸,在得到的新图像中亮度与对比度的乘积落在[6000,10000]范围内的图像,质量最佳。并得到结论:改进型多尺度Retinex算法增强曝光不足的彩色图像,以k=1倍标准差截取后再拉伸得到的图像最好。
改进型多尺度Retinex算法应用于彩色遥感图像去云中,方法是先进行取补色,再应用改进型多尺度Retinex算法,突出云区域中的信息,最后再取补色,这一新方法去除薄云效果最佳。
最后,遥感图像去云方法推广到除去高大建筑物的阴影上。采用边缘提取的方法,改进了闭合区域提取的软件,提出了真断点、准断点的判据,将邻点的邻点命名为特征点,有效地提取图像中的闭合区域,将Retinex增强后的图像相应的区域替代后,复合的图像突出了阴影区域的信息。基于小波变换,尝试了基于小波变换的图像增强方法,利用DSP采用小波变换的算法,用CCS编程语言编写边缘提取的工程文件,采用比较法,在显示屏上一半为所摄图像,另一半为实时提取图像中的边缘的图像,效果好。为研究基于DSP实时去雾的方法做好了准备。
The research work of cloud that makes the image quality lower is more important with the development of the optical images application, in particular, of the remote sensing data application. We can not capture the information from the most remote sensing data because there is cloud. So the methods of removing cloud from the remote sensing image must be researched. There are several methods for removing cloud in some conditions and they suit for back and white remote sensing images, such as the methods of Multi-spectrum image, Multi-image interpolation, Multi-source data fusing, and the method of Homomorphic filtering. The concrete methods of removing cloud for a single remote sensing image without any pre-information need research.
The research of this paper consisted of three aspects, which are described of image elements, neighborhood regions and wavelet transform.
First, the image model of the cloud noise had been build, and the sharp characteristics of the cloud noise had been analyzed. The paper suggested the new method for extracting cloud region and its shadow region. The new method is the method of Huyghens secondary. The local information of the remote sensing images in cloud and its shadow could be protruded by the new method. Considered the gradation various characteristics of the cloud, another method that was the method of higher-degree polynomial curve transform had been suggested. The hidden information in cloud region was exposed by the method.
Second, the original quality of Homomorphic filtering method that removed lower frequency signal of original images was analyzed. The cloud in the remote sensing image is just the lower frequency signal of original images. It was researched that the Retinex theory proposed by E. Land on December 30, 1963. The algorithms of Retinex were studied by this paper. In particular, the Center / Surround algorithm that proposed by D. J. Jobson, Zia-ur Rahman, G. A. Woodell (JRW) was considered. The physics original quality of Retinex had been revealed. The advanced multi scale Retinex (AMSR) algorithm was put forward: After the image enhanced by multi scale Retinex the truncate interval of [μ- kσ,μ+ kσ] near the mean brightnessμin k times standard deviationσrange had been elected and stretched. If the production of the brightness multiply with the contrast degree for the stretched image was in [6 000, 10 000], the stretched image has high quality. As the same time, the conclusion has been proved: The method of highest quality for the underexposure color image was that it selected k=1 time standard deviation range near the mean brightness and stretched after enhanced by multi scale Retinex.
In the process for the application of advanced multi scale Retinex algorithm in remote sensing images, there are three steps. The first step elected the complementary color image of the original image. The second step applied the method of the advanced multi scale Retinex algorithm to enhance the information in dark region that was just the cloud region. The last step elected the complementary color image of the enhanced image by the advanced multi scale Retinex. The results of experiments shown the method was effective.
Finally, two of the application fields of the removing cloud methods had practiced. The cloud regions had been extended to the shadow of the grant builds under the sun. The method of removing cloud had been extended to remove fog, and so on. In the first application, this paper extracted the edge of pyramids in Egypt based on Canny algorithm and programs. The programs were in a software package that developed by our theme group was used to extract the shadow regions in remote sensing images. The shadow regions were placed by the same regions that enhanced by multi scale Retinex algorithm and the more information in the shadow was showed. The software package was improved. The characteristic point idea was proposed and the distinguish method between the real-broken point and quasi-broken point was described. The closed regions in the remote sensing images were extracted effectively. Another application was that the edge details were extracted in real time with wavelet transform based on DSP. The results of extracting edge details that used the project software programmed by CCS were good. The application was general preparing for the issues of removing fog in real time based on DSR
对光学图像去云方法的研究,首先建立了云噪声影像模型,分析了遥感图像中云的特征,基于波的传播原理,提出了用惠更斯次波法提取遥感图像中云区和云影区,采用边缘模糊的方法,增强所提取区域的信息,进而实现遥感图像局部去云和去云影:基于云区渐变的特性,提出了用高次多项式曲线变换法,拉伸云区像素的灰度值,突出了云区图像的信息。
其次基于邻域法分析了同态滤波法的本质,就是在图像中滤去低频信号,正因为云在遥感图像中正好属于低频信息,故同态滤波法也能用于遥感图像去云。深入研究了E.Land在20世纪60年代提出的Retinex思想,以及无数学者在Land的基础上研究获得的各种各样算法,特别研究了工作在NASA和CWM的D.J.Jobson,Zia-ur Rahman,G.A.Woodell(简称JRW)等人的Retinex思想。揭示了Retinex算法的物理本质,提出了改进型多尺度Retinex算法:运用多尺度Retinex算法增强彩色图像后,在其亮度平均值附近以k倍标准差截取,再进行拉伸,在得到的新图像中亮度与对比度的乘积落在[6000,10000]范围内的图像,质量最佳。并得到结论:改进型多尺度Retinex算法增强曝光不足的彩色图像,以k=1倍标准差截取后再拉伸得到的图像最好。
改进型多尺度Retinex算法应用于彩色遥感图像去云中,方法是先进行取补色,再应用改进型多尺度Retinex算法,突出云区域中的信息,最后再取补色,这一新方法去除薄云效果最佳。
最后,遥感图像去云方法推广到除去高大建筑物的阴影上。采用边缘提取的方法,改进了闭合区域提取的软件,提出了真断点、准断点的判据,将邻点的邻点命名为特征点,有效地提取图像中的闭合区域,将Retinex增强后的图像相应的区域替代后,复合的图像突出了阴影区域的信息。基于小波变换,尝试了基于小波变换的图像增强方法,利用DSP采用小波变换的算法,用CCS编程语言编写边缘提取的工程文件,采用比较法,在显示屏上一半为所摄图像,另一半为实时提取图像中的边缘的图像,效果好。为研究基于DSP实时去雾的方法做好了准备。
The research work of cloud that makes the image quality lower is more important with the development of the optical images application, in particular, of the remote sensing data application. We can not capture the information from the most remote sensing data because there is cloud. So the methods of removing cloud from the remote sensing image must be researched. There are several methods for removing cloud in some conditions and they suit for back and white remote sensing images, such as the methods of Multi-spectrum image, Multi-image interpolation, Multi-source data fusing, and the method of Homomorphic filtering. The concrete methods of removing cloud for a single remote sensing image without any pre-information need research.
The research of this paper consisted of three aspects, which are described of image elements, neighborhood regions and wavelet transform.
First, the image model of the cloud noise had been build, and the sharp characteristics of the cloud noise had been analyzed. The paper suggested the new method for extracting cloud region and its shadow region. The new method is the method of Huyghens secondary. The local information of the remote sensing images in cloud and its shadow could be protruded by the new method. Considered the gradation various characteristics of the cloud, another method that was the method of higher-degree polynomial curve transform had been suggested. The hidden information in cloud region was exposed by the method.
Second, the original quality of Homomorphic filtering method that removed lower frequency signal of original images was analyzed. The cloud in the remote sensing image is just the lower frequency signal of original images. It was researched that the Retinex theory proposed by E. Land on December 30, 1963. The algorithms of Retinex were studied by this paper. In particular, the Center / Surround algorithm that proposed by D. J. Jobson, Zia-ur Rahman, G. A. Woodell (JRW) was considered. The physics original quality of Retinex had been revealed. The advanced multi scale Retinex (AMSR) algorithm was put forward: After the image enhanced by multi scale Retinex the truncate interval of [μ- kσ,μ+ kσ] near the mean brightnessμin k times standard deviationσrange had been elected and stretched. If the production of the brightness multiply with the contrast degree for the stretched image was in [6 000, 10 000], the stretched image has high quality. As the same time, the conclusion has been proved: The method of highest quality for the underexposure color image was that it selected k=1 time standard deviation range near the mean brightness and stretched after enhanced by multi scale Retinex.
In the process for the application of advanced multi scale Retinex algorithm in remote sensing images, there are three steps. The first step elected the complementary color image of the original image. The second step applied the method of the advanced multi scale Retinex algorithm to enhance the information in dark region that was just the cloud region. The last step elected the complementary color image of the enhanced image by the advanced multi scale Retinex. The results of experiments shown the method was effective.
Finally, two of the application fields of the removing cloud methods had practiced. The cloud regions had been extended to the shadow of the grant builds under the sun. The method of removing cloud had been extended to remove fog, and so on. In the first application, this paper extracted the edge of pyramids in Egypt based on Canny algorithm and programs. The programs were in a software package that developed by our theme group was used to extract the shadow regions in remote sensing images. The shadow regions were placed by the same regions that enhanced by multi scale Retinex algorithm and the more information in the shadow was showed. The software package was improved. The characteristic point idea was proposed and the distinguish method between the real-broken point and quasi-broken point was described. The closed regions in the remote sensing images were extracted effectively. Another application was that the edge details were extracted in real time with wavelet transform based on DSP. The results of extracting edge details that used the project software programmed by CCS were good. The application was general preparing for the issues of removing fog in real time based on DSR
引文
[1]Glennn D.Hines,Zia-ur Rahman,D.J.Jobson,et al.Real-time Enhanced Vision System.SPIE.2005,5802:127-134
[2]Gu Dongsheng,Yang Nansheng,Pi Defu,et al.A DSP+FPGA based real-time histogram equalization system of infrared image.SPIE.2001,4602:160-165
[3]李小春,王勇,陈鲸.多光谱图像中云层及阴影的检测与消除[J].宇航学报.2004,25(5):555-559
[4]冯春,马建文,戴芹,等.一种改进的遥感图像薄云快速去除方法[J].国土资源共享源遥感.2004,62(4):1-5
[5]王仁礼,戚铭尧,王慧.用于图像融合的HIS变换方法的比较[J].测绘学院学报.2001,17(4):269-272
[6]王虹,时文.基于神经网络的主分量分析及其在图像压缩中的应用研究[J].武汉理工大学学报.2005,29(3):425-428
[7]牛凌宇.多源遥感图像数据融合技术综述[J].空间电子技术.2005,(1):1-10
[8]Peter J.Burt,Edward H.ADELSON.The Laplacian Pyramid as a Compact Image Code[J].IEEE transactions on communications.1983,31(4):532-540]
[9]陶纯堪,陶纯匡,光学信息论[M].北京:科学出版社,2004:24
[10]J.J.McCann.Capturing a Black Cat in Shade:the Past and Present of Retinex Color Appearance Models.2002,SPIE.4662:331-340
[11]E.Land.The Retinex[J].Am.Sci.1964,52:247-264
[12]Alessando Rizzr,Davide Gadia,Daniele Marini.Spectral Information and Spatial Color Computation.SPIE.2005,5667:22-27
[13]E.Land,J.J.McCann.Lightness and Retinex Theory.Journal of the Optical Society of America.1971,61(1):1-11
[14]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell.Properties and Performance of a Center/Surround Retinex[J].IEEE TRANSACTIONS ON IMAGE PROCESSING.1997,6(3):451-462
[15]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.A Multiscale Retinex for Bridging the Gap between Color Images and the Human Observation of Senses.IEEE Transactions on Image Processing.1997,1(7):965-976
[16]B.Thompson,Z.Rahman,S.Park.Retinex Preprocessing for Improved Multi-spectral Image Classification.SPIE.1999,3716:29-39
[17]D.H.Brainard,B.A.Wandell.Analysis of the Retinex theory of color vision[J].J.opt.soc.Am.A.1986,3(10):1651-1661
[18]Gianlugi Ciocca,Daniele Marini,Alessandro Rizzi,et al.On Pre-filtering with Retinex in Color Image Retrieval[J].SPIE,2001,4311:140-146
[19]Hawley K.Rising III.Analysis and generalization of Retinex by recasting the algorithm in wavelets.Journal of electronic Imaging.2004,13(1):93-99
[20]Andrew Moore.A Real-time neural System for Color Constancy[J].IEEE,Transaction on neural networks.1991,2(2):237-247
[21]Tatsumi Watanabe,Yusuhiro Kuwahara,Akio Kojima,et al.Improvement of Color Quality with modified Linear Multi-scale Retinex[J].SPIE-IS&T,2003,5008:59-69
[22]Brian V.Funt,Mark S.Drew.Color Constancy Computation in Near-Mondrian Scenes Using a Finite Dimensional Linear model[J].IEEE,1988,544-549
[23]张荣,刘政凯,詹曙.基于小波变换的多光谱图像压缩方法[J].遥感学报,2000,4(2):100-105]
[24]孟鲁闽,席晶.利用不同校正法进行不同影像间空间配准[J].测绘通报.2003,6:14-15]
[25]郑永安,陈玉春,宋建社,等.基于提升机制小波变换的SAR与多光谱图像融合算法[J].计算机工程.2006,32(6):195-197]
[26]张玉虎,塔西甫拉提,特依拜,等.多源遥感信息融合方法探讨[J].新疆地质.2004,22(3):326-329]
[27]张红蕾,宋建社,张宪伟,等.SAR图像与多光谱图像融合方法研究[J].影像技术.2006,(1):48-51]
[28]谢华美,李荣艳,田艳琴.基于大数遥感图像的薄云去除.北京师范大学学报.2006,42(1):42-46
[29]吴乃龙,袁素云.最大熵方法[M].长沙:湖南科学技术出版社.1991:9
[30]马龙,缪栋.光学影像匹配基准图的滤波方法研究[J].上海航天.2000,(1):27-31
[31]肖志级,黄建军.城市彩色航空影像的边缘模糊Retinex阴影消除[J].中国体视学与图像分析.2004.9(2):95-98
[32]江兴方,陶纯堪.Retinex彩色图像增强理论及其研究进展[J].光学技术.2005,31(增刊):258-260
[33]江兴方,潘国卫,陶纯堪.惠更斯次波法在去云及其阴影中的应用[J].应用光学.2007,28(2):165-168
[34]江兴方,潘国卫,陶纯堪.基于高次多项式曲线的一种遥感图像去云方法[J].激光技术.录用待发表
[35]Daniel J.Jobson,Zia-ur Rahman,Glenn A.Woodell.The statistics of visual representation [J].SPIE.2002,4736:25-35
[36]Soong Der Chen,Abd.Rahman Ramli.Contrast Enhancement using Recursive Mean-Separtate Histogram Equalization for Scalable Brightness preservation.IEEE Transactions on Consumer Electronics.2003.49(4):1301-1308
[37]陈奋,赵惠明,杨健,等.高分辨率遥感影像的云阴影去除.计算机工程与应用.2005,35:180-182
[38]黄峰,周旋,周树道,等.薄云薄雾影响下目标影像自适应增强.红外与激光工程,2005,34(3):324-327
[39]阮秋琦.数字图像处理学[M].北京:电子工业出版社.2001:200
[40]易亨瑜,吕百达,季云松.不同云层背景中目标的识别[J].激光技术.2004,28(2):133-137
[41]Tae Keun Kim,Joon Ki Paik,Bong Soon Kang.Contrast Enhancement System using Spatially Adaptive Histogram Equalization with temporal Filtering.IEEE Transactions on Consumer Electronics,1998,44(1):82-87
[42]Joung Youn Kim,Lee Sup Kim,Seung Ho Hwang.An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization.IEEE transactions on Circuits and Systems for Video technology.2001,11(4):475-484
[43]Nathaniel J.McCaffrey,Francis S.Pantuso.Very Low Cost Real Time Histogram Based Contrast Enhancer Utilizing Fixed-point DSP Processing[J].SPIE 3303:36-43
[44]Sermsak Jaruwatanadilok,Akira lshimaru,Yasuo Kuga.Optical Imaging Through Clouds and Fog.IEEE Transaction on Geosciences and Remote Sensing,Vol.41,No.8.August 2003,41(8):1834-1843.
[45]Stefano Marsi,Giovanni Ramponi and serio Carrato.Image Contrast Enhancement Using a Recursive rational filter[J].IEEE IST 2004.International workshop on Imaging Systems and techniques Stresa,Italy.29-34
[46]G.Ramponi,L.Tenze,s.Carrato,et al.Nonlinear Contrast Enhancement Based on the Retinex Approach.SPIE.2003,5014:169-177
[47]Richard C.Dougal,Clive A.Greated,Alan E.Marson.Then and now:James Clerk Maxwell and Colour[J].Optics & Laser Technology.2006,38:210-218
[48]R.A.Viscarra Rossel,B.Minasny,P.Roudier.Et al.Colour Space Models for Soil Science [J].Science Direct.Geoderma.2006,133:320-337
[49]江兴方,陶纯堪,是度芳.用最大熵方法改善图像质量[J].江苏工业学院学报.2005,17(1):44-47
[50]胡晓峰,吴玲达,老松杨,等.多媒体技术教程[M].北京:人民邮电出版社.2002:45
[51]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.Retinex Processing for Automatic Image Engancement[J].Journal of Electronic Imaging.2004,13(1):100-110
[52]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Impact of Multi-scale Retinex Computation on Performance of Segmentation Algorithms.SPIE.2004,5438:171-182
[53]江兴方,陶纯堪.Retinex彩色图像增强理论的物理思考及其截断区间对图像质量的影响[J].光学技术.2007,33(1):127-12
[54]Canny J.A computational approach to edge detection[J].IEEE-PAMI,1986,8:679-698
[55]U.Meyer-Base,F.Taylor.High-speed Wavelet Implementation with Field-Programmable Logic[J].1999,EPIE,3723.250-261
[56]Amos Talmi.FarAway-shoot video through haze,mist and smoke[J].2005.SPIE,5811:67-74
[57]颜露新,张天序,邹胜.等.用FPGA实现互联的多DSP并行系统结构[J].系统工程与电子技术.2005,27(10):1757-1759
[58]张怡霄,杜惊雷,高福华.等.分数域啁啾滤波及其在数字图像中的应用[J].激光技术. 2003,27(1):78-80
[59]石爱业,徐立中,黄凤辰.一种改进的基于小波变换的遥感图像融合方法[J].仪器仪表学报.2004,25(4):690-691
[60]牟凤云,朱博勤,贺华中.基于小波变换的多源遥感数据融合方法研究[J].国土资源遥感.2003,58(4):30-341
[61]邸凯昌,李德仁,李德毅.基于空间数据发掘的遥感图像分类研究[J].武汉测绘科技大学学报.2000,25(1):42-48]
[62]Jean-luc Starck,Fionn Murtagh,Emmanuel J.Candes,et al.Gray and Color Image Contrast Enhancement by the Curvelet Transform[J].IEEE Transactions on Image processing.2003,12(6):706-716
[63]John P.Oakley,Brenda L.Satherley.Improving Image Quality in poor Visibility Conditions Using a Physical Model for Contrast degradation[J].IEEE Transactions on Image processing.1998,7(2):167-179
[64]Kelly E.Neriani,Travis J.Herbranson,George A.Reis,et al.Visual performance-based image enhancement methodology:an investigation of contrast enhancement algorithms[J].SPIE,6226:1-12
[65]Brian Funt,Florian Ciurea.Control Parameters for Retinex.2002,SPIE,4421:287-290
[66]Laurence Meylan and Sabine S(?)sstrunk.Bio-inspired color image enhancement[J].SPIE,2004,5292:46-56
[67]江兴方,陶纯堪.Retinex彩色图像增强理论及其研究进展[A].2005年全国博士生学术论坛光学工程[C].北京:全国博士生学术论坛委员会.2005:335-339
[68]B.Thompson,Z.Rahman,S.Park.A Multiscale Retinex for Improved Performance in Multi-spectral Image Classification.SPIE.2000,4041:34-44
[69]Nesim Halyo,Zia-ur.Rahman,Stephen K.Park.Information Content in Nonlinear Local Normalization Processing of Digital Images.SPIE.2001,4388:129-142
[70]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell,et al.The Spatial Aspect of Color and Scientific Implications of Retinex images processing.SPIE.2001,4388:117-128
[71]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Multi-sensor Fusion and Enhancement Using the Retinex Image Enhancement Algorithm.SPIE.2002,4736:36-44
[72]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Retinex Processing for automatic Image Enhancement.SPIE.2002,4662:390-401
[73]Glenn Hines,Zia-ur Rahman,Daniel J.Jobson,et al.Multi-image Registration for an Enhanced Vision System.SPIE.2003,5108:231-241
[74]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell.Feature Visibility Limits in the Non-linear Enhancement of Turbid Images.SPIE.2003,5108:24-30
[75]Glenn Hines,Zia-ur Rahman,Daniel J.Jobson,et al.DSP Implementation of the Retinex Image Enhancement Algorithm.SPIE.2004,5438:13-24
[76]Glenn Woodell,Daniel J.Jobson,Zia-ur Rahman,et al.Enhancement of Imagery in Poor Visibility Conditions.SPIE.2005,5778:673-683
[77]Edisson Alban,Vladimir Katkovnik,Karen Egiazarian.Adaptive Window size Gradient Estimation for image Edge Detection[J].SPIE.2003,5014:54-65
[78]Petr Musilek,Madan M.Gupta,Gregory J.Schmidt.Adaptive Fuzzy Approach to Edge Detection.SPIE,3832.1999:109-119
[79]Jun Shen,Wei Shen,dan-Fei Shen.general Theory for Remote Sensing Image Filtering and Edge Detection Based on Orthogonal Function Integration.SPIE,2579:248-258
[80]Feng Xiao,Joyce E.Farrell,Jeffrey M.DiCarlo,et al.preferred color Space for White Balancing[J].SPIE.2003,5017,342-350
[81]Boris Likhterov,Norman S.Kopeika.Motion-blurred Image Restoration using Modified Inverse all-pole Filters[J].Journal of Electronic imaging.2004,13(2):257-263
[82]Sung Cheol Park,Moon Gi Kang.Noise-adaptive Edge-preserving Image Restoration Algorithm[J].Society of Photo-Optical Instrumentation Engineers.2000,39(12):3124-3137
[83]Erkan Besdok.Impulsive Noise Suppression from Images with a Modified two-step Iterative-median Filter[J].Journal of Electronic Imaging.2004,13(4):714-719
[84]Jun-ichi Inoue,kazuyuki Tanaka.Dynamics of the Maximum Marginal Likelihood Hyperparameter estimation in Image Restoration:gradient Descent Versus Expectation and Maximization Algorithm[J].Physical Review.2001,65(016125):1-11
[85]Moira I.Smith,Jamie P.Heather.Review of Image Fusion Technology in 2005[J].SPIE. 2005,5782:29-45
[86]Igor V.Maslov.Image Fusion with the Hybrid Evolutionary Algorithm and Response Analysis[J].SPIE,2005,5813:25-33
[87]Edward j.Bender,Colin E.Reese,gooitzen S.van der Wal.Comparison of Additive Image Fusion vs.Feature-level Image Fusion Techniques for Enhanced Night Driving[J].SPIE,2003,4796:140-151
[88]章毓晋.图像分割[M].北京:科学出版社.200l
[89]李方慧,王飞,何佩琨.TMS320C6000系列DSPs原理与应用(第二版)[M].北京:电子工业出版社.2005
[90]郑红,吴冠.TMS320C54xDSP应用系统设计[M].北京航空航天大学出版社.2002:137
[91]苏显渝,李继陶.信息光学[M].北京:科学出版社.2002
[92]江兴方.近代物理实验(第二版)[M].江苏工业学院.2007
[93]沈涛,宋建社,薛文通.整数到整数小波变换及其DSP实现[J].计算机工程与设计.2005,26(7):1698-1700
[94]任俊,李志能,傅一平.薄雾天气下图像的复原与边缘检测研究[J].计算机辅助设计与图学学报.2005,17(4):694-698
[95]吴传庆,王桥,杨志峰.基于混合像元分解的水体遥感图像去云法[J].遥感学报,2006,10(2):176-183
[96]王彦臣,李树杰,黄廉卿.基于多尺度Retinex的数字X光图像增强方法研究[J].光学精密工程.2006,14(1):70-76
[97]王晓莉,文华,罗予频.基于鲁棒估计的Retinex图像增强方法[J].计算机应用.2006,26(7):1611-1613
[98]郑战辉,韩少红,孙曼,等.小波分解融合在图像去云处理中的应用[J].测绘技术装备.2006,8(1):17-20
[99]周春艳,王萍,郑学芬.基于MATLAB的遥感图像薄云去除[J].西部探矿工程.2006(增刊):224-227
[100]芮义斌,李鹏,孙锦涛.一种图像去薄雾方法[J].计算机应用.2006,26(1):154-156
[101]刘卜,屈有山,李英才,等.采用TMS320C6203的运动点目标检测系统设计[J].光子光报.2006,35(6):950-952
[102]刘斌,彭嘉雄.具有紧支撑正交非张量积小波的图像融合[J].光学学报.2004.24(9):1214-1218
[103]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.A Multiscale Retinex for Color Rendition and Dynamic Range Compression[J].SPIE.1996,2847:183-191
[104]Brian Funt,Florian,John McCann.Tuning Retinex Parameters[J].SPIE.2002,4662:358-366
[105]Firas Hassan,Joan E.Carletta.An Algorithm for the Enhancement of Images of Large Dynamic Range[J].SPIE.2006,6064:606415;1-11
[106]Cristian Munteanu,Agostinho Rosa.Color Image Enhancement Using Evolutionary Principles and the Retinex Theory of Color Constancy[J].IEEE.2001:393-402
[107]Anya Hurlbert,Kit Wolf.The contribution of Local and global Cone-contrasts to Colour Appearance:a Retinex-like Model[J].SPIE.2002,4662:286-297
[108]S.Bouchoux,V.Brost,F.Yang,et al.Implementation of pattern Recognition Algorithm Based on RBF Neural Network[J].SPIE.2002,4791:125-135
[109]C.Steve Suh,Andrew K.Chan.Wavelet-Based technique for Detection of Mechanical Chaos[J].SPIE.2000:267-274
[110]Oleksiy Pogrebnyak,Juan Humberto Sossa Azuela.Fast Algorithm of Byte-to-byte Wavelet Transform for Image Compression Application[J].SPIE.2002:291-301
[111]Te-Ming Tu,Yuh-Chi Lee,Chien-Ping Chang,et al.Adjustable Intensity-hue-Saturation and Brovey Transform Fusion Technique for IKONOS/QuickBird Imagery[J].Optical Engineering.2005,116201:1-10
[112]Deng J X.Decision of ROI scaling value and ROI coding[J].ACTA PHOTONICA SINICA,2006,35(6):944-949
[113]Yah W H,Ma C W,Zhang M,et al.A new way for image fusion based on wavelet transform[J].ACTA PHOTONICA SINICA,2006,35(4):638-640
[114]Zhao X F,He J H,Wei M Z,et al.A new method of getting wake character based image process technology[J].ACTA PHOTONICA SINICA,2006,35(3):443-446
[115]A.Hurlbert.Formal connections between lightness algorithm.J.Opt.Soc,Am.A.1986, 3(10):1684-1693
[116]http://dragon.larc.nasa.gov/retinex/pao/news.html
[117]http://news.shangdu.com/16/2002-09-16/20020916-17133-16.shtml
[118]http://www.hkba-travel.org/world_scenery/outlook_03.htm
[119]http://emis.math.ecnu.edu.cn/journals/NNJ/Reynolds.html
[120]Lei Liu,Benkang Chang.Spectral matching factors between Super S_(25)and New S_(25)Photo Cathodes and reflective radiation of objects.Applied Optics.2004,43(3):616-619
[121]Giovanni Bianco,Alessandro Rizzi.Chromatic Adaptation pre-filtering Effect on Visual based Motion Strategies[J].proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems.2000:2286-2291
[122]Daniele Marini,Alessandro Rizzi.Non-supervised Chromatic Illuminant Corrector for Autonomous Robots[J].IEEE.1997:126-132
[123]Daniele Marini,Alessandro Rizzi,Maurizio Rossi.Color Constancy Measurements for Synthetic Image Generation[J].Journal of Electronic Imaging.1999,8(4):394-403
[124]Alessandro Rizzi,Daniele Marini,Luigi Rovati,et al.Unsupervised Corrections of Unknown Chromatic Dominants Using a Brownian-path-based Retinex Algorithm [J].Journal of Electronic Imaging.2003,12(3):431-441
[125]Daniele Marini,Alessandro Rizzi,Caterina Carati.Color Constancy Effects Measurement of the Retinex Theory[J].SPIE.1998,3647:249-256
[126]Alessandro Rizzi,Carlo Gatta,Daniele Marini.From Retinex to Automatic Color Equalization:Issue in Developing a new Algorithm for Unsupervised Color Equalization [J].Journal of Electronic Imaging.2004,13(1):75-84
[127]Robert B.Staszewski,Roman Staszewski,John L.Wallberg,et al.SoC with an Integrated DSP and a 2.4-GHz RF Transmitter[J].IEEE.2005,1063-8210:1253-1265
[128]Joaquin Cornejo,Yezid Torres.Hybrid JTC using DSP Technology[J].SPIE.2005,5776:340-346
[129]Lihu Chiu,Grant Chang.Embedded Real-Time Image Processing Hardware for Feature Extraction and Clustering[J].SPIE.2003,5082:132-138.
[130]L.Friebe,H.Kloos,J.P.Wittenburg,et al.Multi-DSP-Board for Compact real-Time Synthetic Aperture Radar Systems[J].SPIE.2001,4366:395-399
[131]D.G.Haas,C.L.Siefring,M.M.Baumback.et al.Space-flight Digital Signal Processor System for on-Board Processing of experiment Data[J].Rev.Sci.Instrum.1996,67(10):3751-3754
[132]Iei haijun,Li Dehua,Hu Hanping.High-speed aerial Image processing System Based on DSP[J].SPIE.2001,4555:131-136
[133]Brost V.,Bouchoux S.,yang F.,et al.Real Time Implementation of Face Tracking on DSP TMS320C6x Embedded System[J].SPIE.2003,4948:701-706
[134]Volodymyr I.Ponomaryov,Francisco J.Gallegos funces,Oleksiy b.Pogrebnyak.Real-time Image Filter with Retention of Small-size Details and Complex Noise Mixture[J].SPIE.2002,4666:30-41
[135]Jeremiah Golston,Satish Arora,Ratna Reddy.Optimized Video Decoder Architecture for TMS320C64x DSP Generation[J].SPIE.2003,5022:719-726
[136]Zhang Junju,Qian Yunsheng,Chang Benkang,et al.Sigal Processing of Microbolometer Infrared Focal-plane Arrays[J].SPIE.2005,5640:137-144
[137]Christopher Manning,Mike J.Gross,tim hasgaw,et al.Compact interferometers for chemical and Biological Agent detection |J].SPIE.2004,5268:125-130
[138]倪国强,王毅,方庆喆,等.实时图像融合技术研究的硬件实现[J].红外与激光工程.2002,31(4):342-345
[139]王毅,倪国强,李勇量.基于TMS320C6x的双波段图象高速融合系统[J].中国图象图形学报.2002,7(10):1038-1042
[140]李勇量,倪国强,陈小梅.采用可编程器件实现图像实时融合系统的控制[J].光电工程.2003,30(4):11-14
[141]王毅,倪国强,李勇量.多分辨图像融合算法在DSP系统中的实现[J].北京理工大学学报.2001,21(6):765-769
[142]许廷发,张彬,倪国强.基于多DSP混合结构的Gabor小波神经网络图像目标识别[J].北京理工大学学报.2005,25(11):989-992
[143]江兴方,金龙,陶纯堪.基于MSR和边缘提取的彩色图像融合新方法[J].光电工程.2006,33(3):110-113
[2]Gu Dongsheng,Yang Nansheng,Pi Defu,et al.A DSP+FPGA based real-time histogram equalization system of infrared image.SPIE.2001,4602:160-165
[3]李小春,王勇,陈鲸.多光谱图像中云层及阴影的检测与消除[J].宇航学报.2004,25(5):555-559
[4]冯春,马建文,戴芹,等.一种改进的遥感图像薄云快速去除方法[J].国土资源共享源遥感.2004,62(4):1-5
[5]王仁礼,戚铭尧,王慧.用于图像融合的HIS变换方法的比较[J].测绘学院学报.2001,17(4):269-272
[6]王虹,时文.基于神经网络的主分量分析及其在图像压缩中的应用研究[J].武汉理工大学学报.2005,29(3):425-428
[7]牛凌宇.多源遥感图像数据融合技术综述[J].空间电子技术.2005,(1):1-10
[8]Peter J.Burt,Edward H.ADELSON.The Laplacian Pyramid as a Compact Image Code[J].IEEE transactions on communications.1983,31(4):532-540]
[9]陶纯堪,陶纯匡,光学信息论[M].北京:科学出版社,2004:24
[10]J.J.McCann.Capturing a Black Cat in Shade:the Past and Present of Retinex Color Appearance Models.2002,SPIE.4662:331-340
[11]E.Land.The Retinex[J].Am.Sci.1964,52:247-264
[12]Alessando Rizzr,Davide Gadia,Daniele Marini.Spectral Information and Spatial Color Computation.SPIE.2005,5667:22-27
[13]E.Land,J.J.McCann.Lightness and Retinex Theory.Journal of the Optical Society of America.1971,61(1):1-11
[14]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell.Properties and Performance of a Center/Surround Retinex[J].IEEE TRANSACTIONS ON IMAGE PROCESSING.1997,6(3):451-462
[15]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.A Multiscale Retinex for Bridging the Gap between Color Images and the Human Observation of Senses.IEEE Transactions on Image Processing.1997,1(7):965-976
[16]B.Thompson,Z.Rahman,S.Park.Retinex Preprocessing for Improved Multi-spectral Image Classification.SPIE.1999,3716:29-39
[17]D.H.Brainard,B.A.Wandell.Analysis of the Retinex theory of color vision[J].J.opt.soc.Am.A.1986,3(10):1651-1661
[18]Gianlugi Ciocca,Daniele Marini,Alessandro Rizzi,et al.On Pre-filtering with Retinex in Color Image Retrieval[J].SPIE,2001,4311:140-146
[19]Hawley K.Rising III.Analysis and generalization of Retinex by recasting the algorithm in wavelets.Journal of electronic Imaging.2004,13(1):93-99
[20]Andrew Moore.A Real-time neural System for Color Constancy[J].IEEE,Transaction on neural networks.1991,2(2):237-247
[21]Tatsumi Watanabe,Yusuhiro Kuwahara,Akio Kojima,et al.Improvement of Color Quality with modified Linear Multi-scale Retinex[J].SPIE-IS&T,2003,5008:59-69
[22]Brian V.Funt,Mark S.Drew.Color Constancy Computation in Near-Mondrian Scenes Using a Finite Dimensional Linear model[J].IEEE,1988,544-549
[23]张荣,刘政凯,詹曙.基于小波变换的多光谱图像压缩方法[J].遥感学报,2000,4(2):100-105]
[24]孟鲁闽,席晶.利用不同校正法进行不同影像间空间配准[J].测绘通报.2003,6:14-15]
[25]郑永安,陈玉春,宋建社,等.基于提升机制小波变换的SAR与多光谱图像融合算法[J].计算机工程.2006,32(6):195-197]
[26]张玉虎,塔西甫拉提,特依拜,等.多源遥感信息融合方法探讨[J].新疆地质.2004,22(3):326-329]
[27]张红蕾,宋建社,张宪伟,等.SAR图像与多光谱图像融合方法研究[J].影像技术.2006,(1):48-51]
[28]谢华美,李荣艳,田艳琴.基于大数遥感图像的薄云去除.北京师范大学学报.2006,42(1):42-46
[29]吴乃龙,袁素云.最大熵方法[M].长沙:湖南科学技术出版社.1991:9
[30]马龙,缪栋.光学影像匹配基准图的滤波方法研究[J].上海航天.2000,(1):27-31
[31]肖志级,黄建军.城市彩色航空影像的边缘模糊Retinex阴影消除[J].中国体视学与图像分析.2004.9(2):95-98
[32]江兴方,陶纯堪.Retinex彩色图像增强理论及其研究进展[J].光学技术.2005,31(增刊):258-260
[33]江兴方,潘国卫,陶纯堪.惠更斯次波法在去云及其阴影中的应用[J].应用光学.2007,28(2):165-168
[34]江兴方,潘国卫,陶纯堪.基于高次多项式曲线的一种遥感图像去云方法[J].激光技术.录用待发表
[35]Daniel J.Jobson,Zia-ur Rahman,Glenn A.Woodell.The statistics of visual representation [J].SPIE.2002,4736:25-35
[36]Soong Der Chen,Abd.Rahman Ramli.Contrast Enhancement using Recursive Mean-Separtate Histogram Equalization for Scalable Brightness preservation.IEEE Transactions on Consumer Electronics.2003.49(4):1301-1308
[37]陈奋,赵惠明,杨健,等.高分辨率遥感影像的云阴影去除.计算机工程与应用.2005,35:180-182
[38]黄峰,周旋,周树道,等.薄云薄雾影响下目标影像自适应增强.红外与激光工程,2005,34(3):324-327
[39]阮秋琦.数字图像处理学[M].北京:电子工业出版社.2001:200
[40]易亨瑜,吕百达,季云松.不同云层背景中目标的识别[J].激光技术.2004,28(2):133-137
[41]Tae Keun Kim,Joon Ki Paik,Bong Soon Kang.Contrast Enhancement System using Spatially Adaptive Histogram Equalization with temporal Filtering.IEEE Transactions on Consumer Electronics,1998,44(1):82-87
[42]Joung Youn Kim,Lee Sup Kim,Seung Ho Hwang.An Advanced Contrast Enhancement Using Partially Overlapped Sub-Block Histogram Equalization.IEEE transactions on Circuits and Systems for Video technology.2001,11(4):475-484
[43]Nathaniel J.McCaffrey,Francis S.Pantuso.Very Low Cost Real Time Histogram Based Contrast Enhancer Utilizing Fixed-point DSP Processing[J].SPIE 3303:36-43
[44]Sermsak Jaruwatanadilok,Akira lshimaru,Yasuo Kuga.Optical Imaging Through Clouds and Fog.IEEE Transaction on Geosciences and Remote Sensing,Vol.41,No.8.August 2003,41(8):1834-1843.
[45]Stefano Marsi,Giovanni Ramponi and serio Carrato.Image Contrast Enhancement Using a Recursive rational filter[J].IEEE IST 2004.International workshop on Imaging Systems and techniques Stresa,Italy.29-34
[46]G.Ramponi,L.Tenze,s.Carrato,et al.Nonlinear Contrast Enhancement Based on the Retinex Approach.SPIE.2003,5014:169-177
[47]Richard C.Dougal,Clive A.Greated,Alan E.Marson.Then and now:James Clerk Maxwell and Colour[J].Optics & Laser Technology.2006,38:210-218
[48]R.A.Viscarra Rossel,B.Minasny,P.Roudier.Et al.Colour Space Models for Soil Science [J].Science Direct.Geoderma.2006,133:320-337
[49]江兴方,陶纯堪,是度芳.用最大熵方法改善图像质量[J].江苏工业学院学报.2005,17(1):44-47
[50]胡晓峰,吴玲达,老松杨,等.多媒体技术教程[M].北京:人民邮电出版社.2002:45
[51]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.Retinex Processing for Automatic Image Engancement[J].Journal of Electronic Imaging.2004,13(1):100-110
[52]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Impact of Multi-scale Retinex Computation on Performance of Segmentation Algorithms.SPIE.2004,5438:171-182
[53]江兴方,陶纯堪.Retinex彩色图像增强理论的物理思考及其截断区间对图像质量的影响[J].光学技术.2007,33(1):127-12
[54]Canny J.A computational approach to edge detection[J].IEEE-PAMI,1986,8:679-698
[55]U.Meyer-Base,F.Taylor.High-speed Wavelet Implementation with Field-Programmable Logic[J].1999,EPIE,3723.250-261
[56]Amos Talmi.FarAway-shoot video through haze,mist and smoke[J].2005.SPIE,5811:67-74
[57]颜露新,张天序,邹胜.等.用FPGA实现互联的多DSP并行系统结构[J].系统工程与电子技术.2005,27(10):1757-1759
[58]张怡霄,杜惊雷,高福华.等.分数域啁啾滤波及其在数字图像中的应用[J].激光技术. 2003,27(1):78-80
[59]石爱业,徐立中,黄凤辰.一种改进的基于小波变换的遥感图像融合方法[J].仪器仪表学报.2004,25(4):690-691
[60]牟凤云,朱博勤,贺华中.基于小波变换的多源遥感数据融合方法研究[J].国土资源遥感.2003,58(4):30-341
[61]邸凯昌,李德仁,李德毅.基于空间数据发掘的遥感图像分类研究[J].武汉测绘科技大学学报.2000,25(1):42-48]
[62]Jean-luc Starck,Fionn Murtagh,Emmanuel J.Candes,et al.Gray and Color Image Contrast Enhancement by the Curvelet Transform[J].IEEE Transactions on Image processing.2003,12(6):706-716
[63]John P.Oakley,Brenda L.Satherley.Improving Image Quality in poor Visibility Conditions Using a Physical Model for Contrast degradation[J].IEEE Transactions on Image processing.1998,7(2):167-179
[64]Kelly E.Neriani,Travis J.Herbranson,George A.Reis,et al.Visual performance-based image enhancement methodology:an investigation of contrast enhancement algorithms[J].SPIE,6226:1-12
[65]Brian Funt,Florian Ciurea.Control Parameters for Retinex.2002,SPIE,4421:287-290
[66]Laurence Meylan and Sabine S(?)sstrunk.Bio-inspired color image enhancement[J].SPIE,2004,5292:46-56
[67]江兴方,陶纯堪.Retinex彩色图像增强理论及其研究进展[A].2005年全国博士生学术论坛光学工程[C].北京:全国博士生学术论坛委员会.2005:335-339
[68]B.Thompson,Z.Rahman,S.Park.A Multiscale Retinex for Improved Performance in Multi-spectral Image Classification.SPIE.2000,4041:34-44
[69]Nesim Halyo,Zia-ur.Rahman,Stephen K.Park.Information Content in Nonlinear Local Normalization Processing of Digital Images.SPIE.2001,4388:129-142
[70]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell,et al.The Spatial Aspect of Color and Scientific Implications of Retinex images processing.SPIE.2001,4388:117-128
[71]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Multi-sensor Fusion and Enhancement Using the Retinex Image Enhancement Algorithm.SPIE.2002,4736:36-44
[72]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell,et al.Retinex Processing for automatic Image Enhancement.SPIE.2002,4662:390-401
[73]Glenn Hines,Zia-ur Rahman,Daniel J.Jobson,et al.Multi-image Registration for an Enhanced Vision System.SPIE.2003,5108:231-241
[74]Daniel J.Jobson,Zia-ur Rahman,Gienn A.Woodell.Feature Visibility Limits in the Non-linear Enhancement of Turbid Images.SPIE.2003,5108:24-30
[75]Glenn Hines,Zia-ur Rahman,Daniel J.Jobson,et al.DSP Implementation of the Retinex Image Enhancement Algorithm.SPIE.2004,5438:13-24
[76]Glenn Woodell,Daniel J.Jobson,Zia-ur Rahman,et al.Enhancement of Imagery in Poor Visibility Conditions.SPIE.2005,5778:673-683
[77]Edisson Alban,Vladimir Katkovnik,Karen Egiazarian.Adaptive Window size Gradient Estimation for image Edge Detection[J].SPIE.2003,5014:54-65
[78]Petr Musilek,Madan M.Gupta,Gregory J.Schmidt.Adaptive Fuzzy Approach to Edge Detection.SPIE,3832.1999:109-119
[79]Jun Shen,Wei Shen,dan-Fei Shen.general Theory for Remote Sensing Image Filtering and Edge Detection Based on Orthogonal Function Integration.SPIE,2579:248-258
[80]Feng Xiao,Joyce E.Farrell,Jeffrey M.DiCarlo,et al.preferred color Space for White Balancing[J].SPIE.2003,5017,342-350
[81]Boris Likhterov,Norman S.Kopeika.Motion-blurred Image Restoration using Modified Inverse all-pole Filters[J].Journal of Electronic imaging.2004,13(2):257-263
[82]Sung Cheol Park,Moon Gi Kang.Noise-adaptive Edge-preserving Image Restoration Algorithm[J].Society of Photo-Optical Instrumentation Engineers.2000,39(12):3124-3137
[83]Erkan Besdok.Impulsive Noise Suppression from Images with a Modified two-step Iterative-median Filter[J].Journal of Electronic Imaging.2004,13(4):714-719
[84]Jun-ichi Inoue,kazuyuki Tanaka.Dynamics of the Maximum Marginal Likelihood Hyperparameter estimation in Image Restoration:gradient Descent Versus Expectation and Maximization Algorithm[J].Physical Review.2001,65(016125):1-11
[85]Moira I.Smith,Jamie P.Heather.Review of Image Fusion Technology in 2005[J].SPIE. 2005,5782:29-45
[86]Igor V.Maslov.Image Fusion with the Hybrid Evolutionary Algorithm and Response Analysis[J].SPIE,2005,5813:25-33
[87]Edward j.Bender,Colin E.Reese,gooitzen S.van der Wal.Comparison of Additive Image Fusion vs.Feature-level Image Fusion Techniques for Enhanced Night Driving[J].SPIE,2003,4796:140-151
[88]章毓晋.图像分割[M].北京:科学出版社.200l
[89]李方慧,王飞,何佩琨.TMS320C6000系列DSPs原理与应用(第二版)[M].北京:电子工业出版社.2005
[90]郑红,吴冠.TMS320C54xDSP应用系统设计[M].北京航空航天大学出版社.2002:137
[91]苏显渝,李继陶.信息光学[M].北京:科学出版社.2002
[92]江兴方.近代物理实验(第二版)[M].江苏工业学院.2007
[93]沈涛,宋建社,薛文通.整数到整数小波变换及其DSP实现[J].计算机工程与设计.2005,26(7):1698-1700
[94]任俊,李志能,傅一平.薄雾天气下图像的复原与边缘检测研究[J].计算机辅助设计与图学学报.2005,17(4):694-698
[95]吴传庆,王桥,杨志峰.基于混合像元分解的水体遥感图像去云法[J].遥感学报,2006,10(2):176-183
[96]王彦臣,李树杰,黄廉卿.基于多尺度Retinex的数字X光图像增强方法研究[J].光学精密工程.2006,14(1):70-76
[97]王晓莉,文华,罗予频.基于鲁棒估计的Retinex图像增强方法[J].计算机应用.2006,26(7):1611-1613
[98]郑战辉,韩少红,孙曼,等.小波分解融合在图像去云处理中的应用[J].测绘技术装备.2006,8(1):17-20
[99]周春艳,王萍,郑学芬.基于MATLAB的遥感图像薄云去除[J].西部探矿工程.2006(增刊):224-227
[100]芮义斌,李鹏,孙锦涛.一种图像去薄雾方法[J].计算机应用.2006,26(1):154-156
[101]刘卜,屈有山,李英才,等.采用TMS320C6203的运动点目标检测系统设计[J].光子光报.2006,35(6):950-952
[102]刘斌,彭嘉雄.具有紧支撑正交非张量积小波的图像融合[J].光学学报.2004.24(9):1214-1218
[103]Zia-ur Rahman,Daniel J.Jobson,Gienn A.Woodell.A Multiscale Retinex for Color Rendition and Dynamic Range Compression[J].SPIE.1996,2847:183-191
[104]Brian Funt,Florian,John McCann.Tuning Retinex Parameters[J].SPIE.2002,4662:358-366
[105]Firas Hassan,Joan E.Carletta.An Algorithm for the Enhancement of Images of Large Dynamic Range[J].SPIE.2006,6064:606415;1-11
[106]Cristian Munteanu,Agostinho Rosa.Color Image Enhancement Using Evolutionary Principles and the Retinex Theory of Color Constancy[J].IEEE.2001:393-402
[107]Anya Hurlbert,Kit Wolf.The contribution of Local and global Cone-contrasts to Colour Appearance:a Retinex-like Model[J].SPIE.2002,4662:286-297
[108]S.Bouchoux,V.Brost,F.Yang,et al.Implementation of pattern Recognition Algorithm Based on RBF Neural Network[J].SPIE.2002,4791:125-135
[109]C.Steve Suh,Andrew K.Chan.Wavelet-Based technique for Detection of Mechanical Chaos[J].SPIE.2000:267-274
[110]Oleksiy Pogrebnyak,Juan Humberto Sossa Azuela.Fast Algorithm of Byte-to-byte Wavelet Transform for Image Compression Application[J].SPIE.2002:291-301
[111]Te-Ming Tu,Yuh-Chi Lee,Chien-Ping Chang,et al.Adjustable Intensity-hue-Saturation and Brovey Transform Fusion Technique for IKONOS/QuickBird Imagery[J].Optical Engineering.2005,116201:1-10
[112]Deng J X.Decision of ROI scaling value and ROI coding[J].ACTA PHOTONICA SINICA,2006,35(6):944-949
[113]Yah W H,Ma C W,Zhang M,et al.A new way for image fusion based on wavelet transform[J].ACTA PHOTONICA SINICA,2006,35(4):638-640
[114]Zhao X F,He J H,Wei M Z,et al.A new method of getting wake character based image process technology[J].ACTA PHOTONICA SINICA,2006,35(3):443-446
[115]A.Hurlbert.Formal connections between lightness algorithm.J.Opt.Soc,Am.A.1986, 3(10):1684-1693
[116]http://dragon.larc.nasa.gov/retinex/pao/news.html
[117]http://news.shangdu.com/16/2002-09-16/20020916-17133-16.shtml
[118]http://www.hkba-travel.org/world_scenery/outlook_03.htm
[119]http://emis.math.ecnu.edu.cn/journals/NNJ/Reynolds.html
[120]Lei Liu,Benkang Chang.Spectral matching factors between Super S_(25)and New S_(25)Photo Cathodes and reflective radiation of objects.Applied Optics.2004,43(3):616-619
[121]Giovanni Bianco,Alessandro Rizzi.Chromatic Adaptation pre-filtering Effect on Visual based Motion Strategies[J].proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems.2000:2286-2291
[122]Daniele Marini,Alessandro Rizzi.Non-supervised Chromatic Illuminant Corrector for Autonomous Robots[J].IEEE.1997:126-132
[123]Daniele Marini,Alessandro Rizzi,Maurizio Rossi.Color Constancy Measurements for Synthetic Image Generation[J].Journal of Electronic Imaging.1999,8(4):394-403
[124]Alessandro Rizzi,Daniele Marini,Luigi Rovati,et al.Unsupervised Corrections of Unknown Chromatic Dominants Using a Brownian-path-based Retinex Algorithm [J].Journal of Electronic Imaging.2003,12(3):431-441
[125]Daniele Marini,Alessandro Rizzi,Caterina Carati.Color Constancy Effects Measurement of the Retinex Theory[J].SPIE.1998,3647:249-256
[126]Alessandro Rizzi,Carlo Gatta,Daniele Marini.From Retinex to Automatic Color Equalization:Issue in Developing a new Algorithm for Unsupervised Color Equalization [J].Journal of Electronic Imaging.2004,13(1):75-84
[127]Robert B.Staszewski,Roman Staszewski,John L.Wallberg,et al.SoC with an Integrated DSP and a 2.4-GHz RF Transmitter[J].IEEE.2005,1063-8210:1253-1265
[128]Joaquin Cornejo,Yezid Torres.Hybrid JTC using DSP Technology[J].SPIE.2005,5776:340-346
[129]Lihu Chiu,Grant Chang.Embedded Real-Time Image Processing Hardware for Feature Extraction and Clustering[J].SPIE.2003,5082:132-138.
[130]L.Friebe,H.Kloos,J.P.Wittenburg,et al.Multi-DSP-Board for Compact real-Time Synthetic Aperture Radar Systems[J].SPIE.2001,4366:395-399
[131]D.G.Haas,C.L.Siefring,M.M.Baumback.et al.Space-flight Digital Signal Processor System for on-Board Processing of experiment Data[J].Rev.Sci.Instrum.1996,67(10):3751-3754
[132]Iei haijun,Li Dehua,Hu Hanping.High-speed aerial Image processing System Based on DSP[J].SPIE.2001,4555:131-136
[133]Brost V.,Bouchoux S.,yang F.,et al.Real Time Implementation of Face Tracking on DSP TMS320C6x Embedded System[J].SPIE.2003,4948:701-706
[134]Volodymyr I.Ponomaryov,Francisco J.Gallegos funces,Oleksiy b.Pogrebnyak.Real-time Image Filter with Retention of Small-size Details and Complex Noise Mixture[J].SPIE.2002,4666:30-41
[135]Jeremiah Golston,Satish Arora,Ratna Reddy.Optimized Video Decoder Architecture for TMS320C64x DSP Generation[J].SPIE.2003,5022:719-726
[136]Zhang Junju,Qian Yunsheng,Chang Benkang,et al.Sigal Processing of Microbolometer Infrared Focal-plane Arrays[J].SPIE.2005,5640:137-144
[137]Christopher Manning,Mike J.Gross,tim hasgaw,et al.Compact interferometers for chemical and Biological Agent detection |J].SPIE.2004,5268:125-130
[138]倪国强,王毅,方庆喆,等.实时图像融合技术研究的硬件实现[J].红外与激光工程.2002,31(4):342-345
[139]王毅,倪国强,李勇量.基于TMS320C6x的双波段图象高速融合系统[J].中国图象图形学报.2002,7(10):1038-1042
[140]李勇量,倪国强,陈小梅.采用可编程器件实现图像实时融合系统的控制[J].光电工程.2003,30(4):11-14
[141]王毅,倪国强,李勇量.多分辨图像融合算法在DSP系统中的实现[J].北京理工大学学报.2001,21(6):765-769
[142]许廷发,张彬,倪国强.基于多DSP混合结构的Gabor小波神经网络图像目标识别[J].北京理工大学学报.2005,25(11):989-992
[143]江兴方,金龙,陶纯堪.基于MSR和边缘提取的彩色图像融合新方法[J].光电工程.2006,33(3):110-113