摘要
红外辐射成像检测由于其非接触、快速、一次检测面积大等特点,成为引人注目的无损检测方法。本文对红外辐射成像检测中的关键技术及其定量化问题进行研究,所涉及的主要关键技术有:红外辐射成像检测实验及序列热图的预处理技术;红外辐射成像检测的热传导模型及有限元分析计算;脉冲相位辐射成像检测技术;红外辐射成像检测中的图像融合技术。针对红外辐射成像检测定量化水平不高的问题,分别在时间域、频率域中对缺陷检测的定量化问题开展研究。全文的主要内容如下:
构建了红外辐射成像检测的实验系统,针对热激励源控制、检测参数设置、检测条件及检测结果等,开展红外辐射成像的实验研究。主动式红外辐射检测面临加热不均、检测对象表面发射率、表面状况对检测的影响等问题,为此根据红外图像检测的特点和需要,提出并实现了图像k近邻高斯平滑滤波、缺陷中心位置检测、旋转跟踪最大梯度缺陷边缘检测及改进的判断分析缺陷分割等预处理功能,为进一步的缺陷定量化分析打下基础;首次采用本征模分解这一具有局部自适应分析能力的信号分析方法,对红外辐射检测的热图像进行处理,指出热图像噪声和加热不均的本征模式特征,通过一次本征模分解实现了热图像噪声抑制和加热不均的修正,改善了图像对比度。
在红外辐射热传导分析的基础上,对缺陷深度和面积大小的红外定量检测问题进行实验和有限元模拟计算研究。采用对时间序列图像求强度平均的方法,由信号本身确定检测中激励开始和结束时间点,为分析缺陷与时间信息的关系建立时间基准。分析了缺陷深度与序列图像对比度时间变化的关系,给出了起始分离时间点的概念,提出并实现了根据温度信号随时间的变化确定上述时间点的方法,对缺陷大小、激励强度、激励时间对缺陷深度分析的影响进行研究,验证了根据上述时间点确定缺陷深度的可靠性,并与对比度最大值时间点等进行对比。在缺陷面积大小的定量分析中,根据时间序列图像中缺陷面积大小检测变化的规律,确定缺陷面积大小检测的最佳时间段,根据对实际缺陷温度异常分布及热传导的分析,对半最大对比度宽度方法进行了改进,提高了检测精度。
脉冲相位热成像检测技术是近年来出现的新型红外无损检测技术,由于其抗干扰能力、探测深度缺陷的能力强,引起人们广泛关注。本文对脉冲相位热成像检测技术中频谱分析的有关问题进行研究,指出合理选择采集频率、采集窗口大小要考虑的影响因素;对通过拟合扩展和插值,相应改变采样时间和采样频率,实际上提高了傅立叶变换的窗口长度和频谱范围进行探讨,一定程度上改善了缺陷检测效果;并分别采用组合平滑滤波、分段拟合的方法改善了频谱变换的实际效果。对脉冲相位辐射检测的定量化问题进行研究,采用有限元方法对缺陷深度检测的盲频率理论进行了计算分析;对缺陷面积大小检测中热扩散对相位、振幅、对比度图像的影响及其造成的误差进行分析,总结其规律,指导缺陷的定量化分析工作。
任何一种无损检测技术都有其局限性,探索多种检测方法的融合处理是无损检测的发展方向。针对红外辐射成像检测易受干扰、检测结果解释困难等问题,开展了红外辐射成像检测中可见光与红外图像的像素级图像融合及其应用的研究。首先根据像素级图像融合的要求,进行基于特征点的多模式图像配准研究,采用CCS方法提取角点作为特征点,设计了一种新的形状描述子完成特征点的匹配。在像素级图像融合方法方面,根据红外辐射成像检测的目的和要求,实现了对比度调制融合、金字塔变换法、小波变换法和EMD分解的多分辨图像融合、透明度图像融合等多种图像融合算法。实验和现场检测结果都证明图像融合有助于红外无损检测中的缺陷解释和定位,明晰了检测结果。
Infrared Thermography has been found to be a very valuable nondestructive evaluation (NDE) due to its non-contactness, rapidity, capability of imaging large area. Research on the key technologies and quantitative infrared thermography is carried through in this dissertation. The key technologies include: infrared thermography experiment and pre-processing technology of sequence images, heat conduct model and finite element analysis of infrared thermography, pulsed phase thermography (PPT), and pixel-level image fusion for infrared thermography. On the quantitative infrared thermography, the research is carried through in time and frequency domain respectively. The main contents of the dissertation are as follows:
The experiment system of infrared thermography is set up and experiment studies are carried through on heating stimulator, experiment parameter, experiment condition and result. To remove the influence of uneven heating, emissivity and status of the sample surface, according to the characteristics and needs of infrared thermography, k-neighbor gauss image averaging, defect center location, rotary tracking edge detecting, and improved estimation analysis image segmentation are achieved. This lay a foundation of quantitative infrared thermography. For the first time, an empirical mode decomposition (EMD) method, which is an adaptive decomposition method, is applied to image processing of infrared thermography. Through analysis of mode function of image EMD, the characterizations of noise and uneven heating are given. Using EMD method, the noise and uneven heating are reduced at the same time and the contrast of thermal image is improved. Good result shows this method is simple and effective to overcome noise and uneven heating in infrared thermography.
Experiment and finite element analysis of quantitative evaluation of defect depth and size are carried through based on the heat conduction. Firstly, the time points of beginning and end of stimulation are found out by averaging the intensity of sequence images and the base origination time point is set up for evaluation of defect depth. The relation between defect depth and sequence images contrast changing with time is analyzed. The concepts of initialization separation time point is given. The method of achieving the time points according to temperature changing with time is realized and comparison was made with maximum contrast time point. The influence of defect size, external heat stimulation intensity and duration on acquiring defect depth was analyzed. The reliability of acquiring the defect depth according to the time points above is proved. The changing rule of defect size was found and best measurement time region was given. Based on the abnormity and heat conduction of defect, full width half maximum method is improved and the measurement precision is advanced.
Pulsed Phase Thermography (PPT) is a new infrared nondestructive evaluation method appeared recently. It brings abroad attention due to its advantage of strongly ability of detecting deeper defects and anti-disturbing. In this paper, The problems of FFT(fast Fourier Transform) of PPT were studied. The key factors for choosing the sampling frequency and truncation were given. This paper also studies how to change the value of sampling frequency and window width through fitting extend and interpolation methods. And, to a certain extent, the result of measurement is improved. The result of fourier transform was improved practically by combining low-pass filters and subsection curve fitting. The theory of phase blind frequency with defect depth of the quantitative pulsed phase thermography is studied through finite element analysis. Finally, the influence and error analysis of thermal diffusion on phase, amplitude and contrast image are studied .
No NDT is perfect and it is the developing orientation of NDT to combine different NDTs. In this paper, for reducing noise and exactly interpretation of thermography, the pixel-level image fusion of infrared light and visible light image for infrared thermography and its application are studied. Firstly in the pixel-level image fusion, different mode image registration has been done based on feature corners. The corners and curves relative to each corner are extracted using the CSS (Curvature Scale Space) method. A new shape context descriptor for each corner is given as the criterion to match the corners. According to the purpose and need of infrared thermography, fusion methods of contrast modulation fusion , multi-scale fusion methods of Laplacian pyramid, wavelet transform and EMD, transparent fusion are studied. The experimental and application results indicate image fusion for infrared thermography can facilitate defect location and interpretation of inspection results.
引文
[1]张俊哲.无损检测技术及其应用.北京:科学出版社,1993.
[2]李家伟,陈积憋.无损检测手册.北京:机械工业出版社,2002.
[3] Xavier P.V. Maldague,Patrick O Moore.Nondestructive Testing Handbook Infrared and Thermal Testing.American Society for Nondestructive Testing,2001.
[4] Xavier P.V.Maldague.Theory and Practice of Infrared Technology for Nondestructive Testing. New York,John Wiley&Sons, 2001.
[5] N.P. Avdelidis. A look on thermography: from passive to active NDT & E surveys.SPIE , 2007, 6541:654115-1-9.
[6] Busse G. Optoacoustic and Photothermal Material Inspection Techniques. Appl. Optics., 1982, 21(1):107–110.
[7] Rosencwaig A, Busse G. High-Resolution Photoacoustic Thermal-Wave Microscopy. Appl. Phys. Lett., 1980,36(9):725–727.
[8] Thomas R.L.,Pouch J. J.,Wong Y.H., et al. Subsurface Flaw Detection in Metals by Photoacustic Microscopy. J. Appl.Phys., 51(2):1152–1156.
[9]张淑仪.光声热波成像及其应用.物理学进展,1996, 16(3,4):439-448.
[10] Joseph N. Zalamedaa, Nik Rajicb, William P. Winfreec. A comparison of image proceesing algorithms for thermal nondestructive evaluation. Thermosense XXV. SPIE,2003, 5073: 374-385.
[11] Takahide Sakagami,Shiro Kubo,Takeshi Endo. Development of a new processing technique of sequential temperature data after pulse heating for quantitative nondestructive testing. Thermosense XXVI,SPIE,2004, 5405: 357-365.
[12] N.P.Avdelidis, D.P.Almond, A.Dobbinson, et al.Aircraft composites assessment by means of transient thermal NDT , Progress in Aerospace Sciences,2004,40 143-162.
[13] Favro LD,Newaz GM,Thomas RL,et al.Progress in thermosonic crack detection for Nondestructive Evaluation.DARPA Prognosis Bidder’s Conference,USA,2002,25-26.
[14] N.P.Avdelidis, C.Ibarra-Castanedo, X.Maldague, et al.A thermographic comparison study for the assessment of composite patches .Infrared Physics Technology ,2004, 45:291-299.
[15]洪毅,缪鹏程,张仲宁,等.超声红外热像技术及其在无损检测中的应用.南京大学学报(自然科学),2003,39(4):547-552.
[16] John W Wilson ,Gui Yun Tian. Pulsed electromagnetic methods for defect detection and characterisation. NDT & E International, 2007, 40(4):275-283.
[17] C. Ibarra-Castanedo, F. Galmiche, A. Darabi, X. Maldague. Thermographic non- destructive evaluation: overview of recent progress. Thermosense XXX. SPIE. 2003, 5073: 450-459.
[18] Mohammed A. Omar, Yi Zhou. A quantitative review of three flash thermography processing routines. Infrared Physics & Technology. 2008,51(4):300-306.
[19] Ibarra-Castanedo C., González D., Galmiche F., et al. Discrete signal transforms as a tool for processing and analyzing pulsed thermographic data. SPIE,2007,6205:620514-1-12.
[20] Shapard S, Lhota J, Rubadeux B, et al. Reconstruction and enhancement of active thermographic image sequences. Opt. Eng. ,2003, 42(5):1337-1342.
[21] X. Maldague,Marinetti. S. Pulsed Phase Infrared Thermography. J. Appl. Phys. 1996, 79(5):2694-2698.
[22] Hernán D. Benítez, Clemente Ibarra-Castanedo, Abdel Hakim Bendada,et al. Definition of a new thermal contrast and pulse correction for defect quantification in pulsed thermography. Infrared Physics & Technology, 2008, 51(3):160-167.
[23] N. Rajic. Principal component thermography for flaw contrast enhancement and flaw depth characterisation in composite structures Composite Structures. 2002,58:521–528.
[24] Marinetti S., Grinzato E., Bison P.G, et al. Statistical analysis of IR thermographic sequences by PCA. Infrared Phys. & Technol., 2005,46:85-91.
[25] M.Omar, M.I.Hassan, K.Saito, R.Alloo.IR self-referencing thermography for detection of in-depth defects.Infrared Physics & Technology,2005,46:283-289.
[26] C.Ibarra-Castanedo, D. Gonzalez, M. Klein, et al. Infrared image processing and data analysis. Infrared Physics & Technology, 2002, 46:75-83.
[27] Hernán D.Benítez, Clemente Ibarra-Castanedo, Abdel Hakim Bendada,et al.Differentiated absolute phase contrast algorithm for the analysis of pulsed thermographic sequences. Infrared Physics & Technology,2006,48:16-21.
[28] N P Avdelidis, D P Almond. Through skin sensing assessment of aircraft structures using pulsed thermography.Journal of NDT&E International,2004, 37(5):353-359.
[29] N P Avdelidis, B C Hawtin, D P Almond.Transient thermography in the assessment of defects of aircraft composites. Journal of NDT&E International, 2003,36(6):433-439.
[30] Takahide Sakagami, Shiro Kubo. Quantitative nondestructive evaluation of delamination damage in CFRP pressure vessels for space use . SPIE, 2007,6205: 62051A1-8.
[31] K. Elliott Cramera, William P. Winfreea,et al. Status of thermal NDT of space shuttle materials at NASA. SPIE, 2007,6205:62051B1-8.
[32]薛书文,宗明成,丁铁英,等.利用红外成像技术检测金属内部近表缺陷.红外与毫米波学报, 1998, 17(6):424-428.
[33]梅林,陈自强,王裕文,等.脉冲加热红外热成像无损检测的有限元模拟及分析.西安交通大学学报,2000,34(1):66-70.
[34]梅林,吴立德,王裕文.脉冲加热红外无损检测中的图像处理,红外与毫米波学报,2002,21(5):372-376.
[35]郭兴旺,刘颖韬,郭广平,等.脉冲相位法及其在复合材料无损检测中的应用.北京航空航天大学学报,2005,31(10):1049-1053.
[36]郭兴旺,刘颖韬,郭广平,等.红外无损检测加热不均时的图像处理方法.北京航空航天大学学报,2005,31(11):1204-1207.
[37]郭兴旺, Vavilov V,郭广平,等.复合材料红外无损检测的建模分析和热像处理.北京航空航天大学学报, 2004,30(4):363-369.
[38]王永茂,王飒爽,马宁,等.缺陷深度脉冲热像检测新方法.无损检测, 2004,26(3):124–126.
[39]王迅,金万平,张存林,等.红外热波无损检测技术及其进展.无损检测, 2004,26(10):497-501.
[40] C.Ibarra-Castanedo, X. Maldague. Defect Depth Retrieval from Pulsed Phase Thermographic Data on Plexiglas and Aluminum Samples. Thermosense XXXI, SPIE 2004,5405:523-531.
[41] A.R Hamzah, P Delpech, M.B Saintey, et al. An experimental investigation of defect sizing by transient thermography. Insight ,1996,38(3):167-71.
[42] M. Omar, M. Hassan, K. Saito. Optimizing thermography depth probing with a dynamic thermal point spread function. Infrared Phys&Tech,2005,46(6): 506-514.
[43] Andreas Mandelis, Lena Nicolaides, Yan Chen. Structure and the reflectionless/refractionless nature of parabolic diffusion-wave fields. Physical Review Letters,2001, 87(2): 0208011-4.
[44] Lena Nicolaides, Andreas Mandelis.Experimental and image-inversion optimization aspects of thermal-wave diffraction tomographic microscopy. Optics Express, 2000,7(13):519-532.
[45]吕跃凯,张淑仪,周庆标.基于光声光热检测的反演技术在热波成像及缺陷分析方面的应用.自然科学进展,2001,11(3):232-237.
[46] W.Bai, B S Wong.Thermal wave scattering from subsurface defects in plates with finite thickness under convective environments Meas.Sci.Technol. 2002,13(5):700–705.
[47] M. Krishnapillai, R. Jones, I.H.Marshall , et al.NDTE using pulse thermography: Numericalmodeling of composite subsurface defects. Composite Structures,2006,75:241-249.
[48] M.Krishnapillai,R.Jones, I.H.Marshall, et al.Thermography as a tool for damage assessment. Composite Structures,2005,67:149–155.
[49] Balageas D L, Krapez J C, Cielo P. Pulsed photothermal modeling of layered materials. Appl.Phys., 1986,59(2), 348-357.
[50] S.Lugin, U.Netzelmann. A defect shape reconstruction algorithm for pulsed thermography. NDT&E International,2007,40:220-228.
[51]杨小林,代永朝,李艳红,等.红外热波技术在飞机复合材料损伤检测中的应用.无损检测,2007,29(4):200-202.
[52] D.P. Almond, S.K. Lau. Defect sizing by transient thermography. I: an analytical treatment. Journal of Physics D: Applied Physics,1994,27:1063-1069.
[53] M.B.Saintey, D.P.Almond. Defect sizing by transient thermography. II: a numerical treatment, Journal of Physics D:Applied Physics,1995,28:2539-2546.
[54] N.Ludwig , P.Teruzzi. Heat losses and 3D diffusion phenomena for defect sizing procedures in video pulse thermography. Infrared Physics&Technology, 2002,43:297-301
[55] Friedrich K,Haupt K,Walther H G. Definition,resolution,and contrast in photothermal imaging.J.Appl.Phys. 1992,72(8):3759-3764.
[56] Pilla M.,Klein M.,Maldague X.,et.al.New Absolute Contrast for Pulsed Thermography.Proc.7th Conference on Quantitative InfraRedThermography (QIRT), 2002.
[57] Huang,N.E.,Shen,Z.,Long,S.R,et.al. The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis.Proc. R. Soc. A 454:903～995.
[58] Huang,N.E.,Shen,Z.,Long,S.R. . A New View of Nonlinear Water Waves: the Hilbert Spectrum. Ann Rev Fluid Mech,1999,31:417-457.
[59]钟佑明,秦树人,汤宝平.一种振动信号新变换法的研究.振动工程学报,2002,15(2):233-235.
[60]宋平舰,张杰.二维经验模分解在海洋遥感图像信息分离中的应用.高技术通讯,2001,9:62-67.
[61] Huang D J, Zhao J P,Su J L.On the extending in the Hilbert-Huang Transform. Progress in Coastal Engineering and Oceanography, Coastal Oceanography of Asian Seas, Korean Society of Coastal and Ocean Engineers,1999, Vol.1:81-92.
[62]邓拥军,王伟,钱成春,等.EMD方法及Hilbert变换中的边界问题的处理.科学通报,2001,46(3):257-263.
[63]黄大吉,赵进平,苏纪兰.希尔伯特-黄变换的端点延拓.海洋学报,2003,25(1):1-11.
[64]张郁山,梁建文,胡聿贤.应用自回归模型处理EMD方法中的边界问题.自然科学进展,2003,13(10):1054-1059.
[65]乐静,郭俊杰、朱虹.基于EMD和Snakes模型信息融合的表面缺陷检测方法.仪器仪表学报,27(12):1664-1669.
[66]沈传经,沈璐蝉,吴子静.热传导.北京:高等教育出版社,1992.
[67]俞昌铭.热传导及其数值分析.北京;清华大学出版社,1981.
[68] Sung Quek, Darryl Almond, Luke Nelson,et al. A novel thermal wave signal reconstruction technique for defect detection in lock-in thermography.Meas. Sci. Technol., 16 (2005):1223-1233.
[69] Aamodt L C,Maclachlan J W,Murphy J C . Analysis of characteristic thermal transit times for time-resolved infrared radiometry studies of multilayered coatings . J.Appl.Phys. 1990,68(12):6087-6097.
[70] Tapio T,Rantala ,Juhani Levoska. A numerical simulation method for the laser-induced temperature distribution. J.Appl.Phys. 1989,65(12):4475-4479.
[71]谭建国.使用ANSYS6.0进行有限元分析.北京:北京大学出版社,2002.
[72] Steven Shepard, James Lhota, David Wang, et al. Depth and spatial resolution enhancement using thermographic signal reconstruction. Proceedings of 6th Far-East Conference on NDT(FENDT’02), 2002: 279-284.
[73]刘波,张存林.基于热波无损检测的缺陷深度检测和边缘识别.首都师范大学学报(自然科学版),2006,27(5):22-15.
[74] Wu D. ,Bussse G. Lock-in Thermography for NonDestructive Evaluation of Materials. Rev. Gén. Therm., 1998,37:693-703.
[75] Meola C.,Carlomagno G. M.,Squillace A.et al.Nondestructive Control of Industrial Materials by Means of Lock-In Thermography. Meas.Sci.Technol., 13:1583-1590.
[76] Balageas D L,Deom A A,Boscher D M. Characterization and nondestructive testing of carbon-epoxy composites by a pulsed photothermal method. Materials Evaluation, 1987:45(4),461-465.
[77] Milne J. M. , Reynolds W. N. The Non-Destructive Evaluation of Composites and other Materials by Thermal Pulse Video Thermography.SPIE, 1984,Thermosense VII, 520:119-122.
[78] Parker W.J., Jenkins R.J., Butler C.P. et al. Flash Method of Determining Thermal Diffussivity, Heat Capacity, and Thermal Conductivity. J. Appl. Phys., 1961,32(9):1679-1684.
[79] Favro L. D., Han X, Kuo P. K. et al. Imaging the early time behavior of reflected thermal wave pulses. Thermosense XVII,SPIE, 1995, 2473:162-166.
[80] Giorleo G. ,Meola C. Comparison between Pulsed and Modulated Thermography in Glass-Epoxy Laminates. NDT&E Int., 2002,35(5):287-292.
[81] Marinetti S., Plotnikov Y. A., Winfree W. P., et al. Pulse phase thermography for defect detection and visualization, Thermosense XXI,SPIE, 1999, 3586:230-238.
[82] Clemente Ibarra-Castanedo, Marc Genest, Stéphane Guibert, et al. Inspection of aerospace materials by pulsed thermography, lock-in thermography and vibrothermography: A comparative study. SPIE, 2007, 6541:116-1-9.
[83]李洪志.信息融合技术.北京:国防工业出版社,1996.
[84]毛士艺,赵巍.多传感器图像融合技术综述.北京航空航天大学学报,2002,28(5):512-517.
[85] Gros X.E., P. Strachan, D.W. Lowden, et al. NDT data. fusion. Proceedings 6th European Conference on NDT. 1994. Nice, France.
[86] Gros X.E.. A review of NDT data fusion processes and applications. Insight 1997. 39(9): 652-657.
[87] Avdelidis, N.P., E.T. Delegou, D.P. Almond, et al. Surface roughness evaluation of marble by 3D laser profilometry and pulsed thermography. NDT & E International, 2004. 37(7): 571-575.
[88] Dessendre, M.F.Thevenot, A.Liot, et al. NDT and CAD data fusion for diagnosis assistance and diffusion bonding improvement. Congress on Nondestructive Testing, 1997. Nantes, France.
[89] Gros, X.E., J. Bousigue, K. Takahashi. NDT data fusion at pixel level. NDT & E International, 1999. 32(5): 283-292.
[90] Jaein Lim. Data Fusion for NDE Signal Characterization(PhD) . 2001, Iowa State University, USA.
[91] B. Zitová, J. Flusser. Image registration methods: a survey. Image and vision Computing, 2003,21:997-1000.
[92]周海芳,刘光明,郑明玲,等.遥感图像自动配准得串行与并行策略研究.国防科技大学学报,2004,26(2):56-61.
[93]谈泉,林家瑞.多模态医学图像融合技术的研究与进展.国际生物医学工程杂志,2006,29(3):158-187.
[94] F. Mokhtarian , R. Suomela. Robust image corner detection through curvature scale space. IEEE Trans on Pattern Analysis and Machine Intelligence, 1998, 20(12):1376-1381.
[95] X.C. He , N.H.C. Yung. Curvature Scale Space Corner Detector with Adaptive Threshold andDynamic Region of Support. Proceedings of the 17th International Conference on Pattern Recognition, 2004,2:791-794.
[96] S. Belongie, J. Malik, J. Puzicha. Shape Matching and Object Recognition Using Shape Contexts. IEEE Trans. Pattern Analysis and Machine Intelligence, 2002, 2(4):509-522.
[97] C.Schmid, R.Mohr. Local grayvalue invariants for image retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(5):530-535.
[98] K. Mikolajczyk, C. Schmid. A performance evaluation of local descriptors. IEEE Trans. On PAMI, 2005, 27(10):1615-1630.
[99]林晓梅,魏巍,李琏.多模态图像配准技术.计算机测量与控制,2006,14(9): 12227-1229.
[100]夏明革,何友,欧阳文.像素级图像融合方法与融合效果评价.遥感技术与应用,2002,4:224-229.
[101]刘松涛,周晓东.图像融合技术研究的最新进展.激光与红外,2006,36(8):627-631.
[102]胡钢,刘哲,徐小平,等.像素级图像融合技术的研究与进展.计算机应用研究,2008,25(3):650-655.
[103]晁锐,张科,李言俊.像素级多分辨图像融合技术概述.系统工程与电子技术,2004,26(1):137-141.
[104]刘贵喜,杨万海.基于多尺度对比度塔的图像融合方法及性能评价.光学学报,2001,21(11):1336-1342.
[105]周朋,奚日辉,宋玲玲,等.基于小波变换的医学图像融合技术的实现.中国图象图形学报,2006,11(11):1720-1723.
[106] Toet, A., L.J. van Ruyven, and J.M. Valeton. Merging thermal and visual images by a contrast pyramid. Optical Engineering,1989,28(7):789–792.
[107]李玲玲,周成平,丁明跃,等.一种基于多尺度分解的多传感器图像融合方法.华中科技大学学报(自然科学版) 31(4):82-84.
[108] Stephane G.Mallat. A Theory for Multiresolution Signal Decomposition:The Wavelet Representation. IEEE Transactions on pattern analysis and machine intelligence, 1989,11:674-693.
[109]刘贵喜,赵曙光,陈文锦.红外与可见光图像融合的多分辨率方法.光电子·激光,2004,15(8),980-984.
[110]陶观群,李大鹏,陆光华.基于小波变换的不同融合规则的图像融合研究.红外与激光工程,2003,32(2),173-177.
[111]王坚,张继贤,刘正军,等.基于经验模态分解的高分辨率影像融合.遥感学报,2007,11(1):55-61.
[112]向世明. Visual C++数字图像与图形处理.北京:电子工业出版社, 2002
[113] Temkin B., S. Vaidyanath, E. Acosta. A high accuracy, landmark-based, sub-pixel level image registration method. International Congress Series. CARS 2005: Computer Assisted Radiology and Surgery, 2005. 1281:254-259.
[114] Petrovic, V.S. Multilevel image fusion, in Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications. Proceedings of Society of Photo-Optical Instrumentation Engineers: Bellingham, 2003, 87-96.
[115] Wang, Z., D. Ziou, C. Armenakis, et al. A comparative analysis of image fusion methods. IEEE Transactions on Geoscience and Remote Sensing, 2005. 43(6): 1391-1402.