遥感图像融合方法研究
|
摘要
遥感图像融合研究作为图像融合领域的一个重要分支,主要是研究如何综合利用不同航空遥感传感器所获取的图像信息,产生新的图像,以获取对同一事物或目标更为全面、客观及本质的认识。近二十年来,引起了世界范围内的广泛关注和研究热潮,成为解决海量数据的一种有效手段,尤其是随着IKONOS、Quick Bird、SPOT-5等高分辨率遥感卫星的相继发射,遥感卫星图像的空间分辨率得到了很大的提高,使得高分辨率遥感图像的应用范围更加广泛。遥感图像融合的目的是充分利用多个待融合源图像中包含的冗余信息和互补信息,将这些信息智能化合成,产生比单一图像信息更精确、更可靠的描述和判决,融合后的图像应该更适合于人类视觉感知或计算机后续处理。本文主要针对高空间分辨率全色图像和多光谱图像的融合方法进行了研究。主要工作如下:
(1)首先讨论了遥感图像融合的历史发展和研究现状,综述了常用的遥感图像融合方法,并比较了各种方法的特点。
(2)图像预处理是进行融合前非常重要的一个阶段,其误差大小直接关系到融合图像的质量,因此,图像预处理是遥感图像融合的前提和基础。本文概述了图像预处理的方法,对遥感图像的几何校正、图像配准和直方图匹配进行了简要的介绍。本文从主观和客观两个方面介绍了目前对融合图像的评价标准,特别在客观评价标准上,分别从单一融合图像的统计特征、融合图像与标准参考图像的关系和融合图像与原始图像的关系三个方面对评价参量进行了分类总结。
(3)小波分析具有多分辨率分析特征,小波在图像分析和处理方面具有很大的优越性,在分析总结了前人的融合算法的基础上,提出了将小波变换应用到遥感图像融合中。由于图像的局部特征往往不是由一个像素所能表征的,它是由某一局部区域的多个像素来体现的,同时,通常图像中某一局部区域内的各像素之间往往有较强的相关性,因此,这种基于像素的融合规则带有很大的片面性,其融合效果也有待改善。提出了基于区域能量的融合方式可以克服上面所说的片面性,而且可以获得更好的视觉效果,使融合图像细节更丰富,更清晰。为了最大限度的保留两幅图像中的重要信息,对多光谱和高分辨率遥感图像来说,既要保留原多光谱图像中的地物光谱信息,又要引入高分辨率图像中的细节纹理信息,提出了一种基于小波变换的自适应融合新算法。通过实验验证了该方法的有效性。
(4)Contourlet是一种新的多尺度几何分析工具,比小波变换更加适合分析二维图像中的曲线或直线状的边缘特征,而且具有更高的逼近精度和更好的稀疏表达能力。本文在研究了Contourlet变换原理和性质的基础上,提出了基于Contourlet变换的图像融合方法,将全色图像和多光谱图像进行Contourlet分解,然后在相应尺度上利用融合规则将Contourlet系数进行融合,最后进行重构得到融合图像。同时提出了一种基于小波-Contourlet变换的融合新算法,以及基于Contourlet变换的自适应融合新算法。实验结果验证了该方法的有效性。
As an important branch of the image fusion, remote sensing image fusion mainly investigates how to integrate image information from the different remote sensing sensors, and generate new images in order to get more complete, objective and essential cognition for the same thing or target. In recent twenty years, it has been a very popular research area, and becomes efficient means to solve the large number data. Especially with the launch of high-resolution remote sensing satellite like IKONOS, Quick-Bird and SPOT-5, the resolution of remote sensing image is higher than before, and the application of the remote sensing images have been more useful. The purpose of image fusion is to utilize the complementary and redundant information in multi-source images, to synthesize information intelligently, and to produce more compete and more reliable description and decision than one image, in order that the fused image should be more suitable for human visual perception or computer further processing. In this paper, most of the research works focus on the fusion method between panchromatic (Pan) image and multispectral (MS) images. The following are the main contents:
(1) The developing of history and research situation of remote sensing fusion are discussed, and many traditional remote sensing fusion algorithms are summarized and compared.
(2) Image preprocessing technique is a very important stage before fusion, its error directly related to the quality of the fusion image, therefore, image preprocessing is the prerequisite and basis for remote sensing image fusion. This paper briefly summarizes the image preprocessing techniques and introduces the geometry correction, image registration and histogram matched. This paper introduces the subjective and objective evaluation criteria, especially on the objective evaluation criteria, the evaluation parameters are classified from three aspects which are the statistic characteristics of a single fusion image, the relationship between the fusion image and the standard reference image, and the relationship between the fusion image and the original images.
(3)Wavelet analysis has multi-resolution characteristics, and has been widely used in the image fusion field. In the paper analylsis the used method in the image fusion field by wavelet, So in this part a image rule of pixel and the image rule of region energy was proposed,and which would select coefficients auto-adapted,which solved the question simultaneously. and the experimental results show the effectiveness of the method.
(4)Contourlet is more appropriate for analyzing the image edges such as curve or linear characteristics than wavelet transform, and it has better approximation precision and sparsity description. In this paper, the second generation Contourlet transform theory and property are researched, and the image fusion method based on the second generation Contourlet transform is proposed, the panchromatic image and multi-spectral images are decomposed using Contourlet transform, then the Contourlet coefficients are fused with the fusion regular in the corresponding scales, and finally the fused coefficients are reconstructed to obtain fusion images, the image rule of self-adaptive was proposed,and which would select coefficients auto-adapted,which solved the question simultaneously.Remote sensing images are taken as experimental data, and the experimental results show the effectiveness of the method.
(1)首先讨论了遥感图像融合的历史发展和研究现状,综述了常用的遥感图像融合方法,并比较了各种方法的特点。
(2)图像预处理是进行融合前非常重要的一个阶段,其误差大小直接关系到融合图像的质量,因此,图像预处理是遥感图像融合的前提和基础。本文概述了图像预处理的方法,对遥感图像的几何校正、图像配准和直方图匹配进行了简要的介绍。本文从主观和客观两个方面介绍了目前对融合图像的评价标准,特别在客观评价标准上,分别从单一融合图像的统计特征、融合图像与标准参考图像的关系和融合图像与原始图像的关系三个方面对评价参量进行了分类总结。
(3)小波分析具有多分辨率分析特征,小波在图像分析和处理方面具有很大的优越性,在分析总结了前人的融合算法的基础上,提出了将小波变换应用到遥感图像融合中。由于图像的局部特征往往不是由一个像素所能表征的,它是由某一局部区域的多个像素来体现的,同时,通常图像中某一局部区域内的各像素之间往往有较强的相关性,因此,这种基于像素的融合规则带有很大的片面性,其融合效果也有待改善。提出了基于区域能量的融合方式可以克服上面所说的片面性,而且可以获得更好的视觉效果,使融合图像细节更丰富,更清晰。为了最大限度的保留两幅图像中的重要信息,对多光谱和高分辨率遥感图像来说,既要保留原多光谱图像中的地物光谱信息,又要引入高分辨率图像中的细节纹理信息,提出了一种基于小波变换的自适应融合新算法。通过实验验证了该方法的有效性。
(4)Contourlet是一种新的多尺度几何分析工具,比小波变换更加适合分析二维图像中的曲线或直线状的边缘特征,而且具有更高的逼近精度和更好的稀疏表达能力。本文在研究了Contourlet变换原理和性质的基础上,提出了基于Contourlet变换的图像融合方法,将全色图像和多光谱图像进行Contourlet分解,然后在相应尺度上利用融合规则将Contourlet系数进行融合,最后进行重构得到融合图像。同时提出了一种基于小波-Contourlet变换的融合新算法,以及基于Contourlet变换的自适应融合新算法。实验结果验证了该方法的有效性。
As an important branch of the image fusion, remote sensing image fusion mainly investigates how to integrate image information from the different remote sensing sensors, and generate new images in order to get more complete, objective and essential cognition for the same thing or target. In recent twenty years, it has been a very popular research area, and becomes efficient means to solve the large number data. Especially with the launch of high-resolution remote sensing satellite like IKONOS, Quick-Bird and SPOT-5, the resolution of remote sensing image is higher than before, and the application of the remote sensing images have been more useful. The purpose of image fusion is to utilize the complementary and redundant information in multi-source images, to synthesize information intelligently, and to produce more compete and more reliable description and decision than one image, in order that the fused image should be more suitable for human visual perception or computer further processing. In this paper, most of the research works focus on the fusion method between panchromatic (Pan) image and multispectral (MS) images. The following are the main contents:
(1) The developing of history and research situation of remote sensing fusion are discussed, and many traditional remote sensing fusion algorithms are summarized and compared.
(2) Image preprocessing technique is a very important stage before fusion, its error directly related to the quality of the fusion image, therefore, image preprocessing is the prerequisite and basis for remote sensing image fusion. This paper briefly summarizes the image preprocessing techniques and introduces the geometry correction, image registration and histogram matched. This paper introduces the subjective and objective evaluation criteria, especially on the objective evaluation criteria, the evaluation parameters are classified from three aspects which are the statistic characteristics of a single fusion image, the relationship between the fusion image and the standard reference image, and the relationship between the fusion image and the original images.
(3)Wavelet analysis has multi-resolution characteristics, and has been widely used in the image fusion field. In the paper analylsis the used method in the image fusion field by wavelet, So in this part a image rule of pixel and the image rule of region energy was proposed,and which would select coefficients auto-adapted,which solved the question simultaneously. and the experimental results show the effectiveness of the method.
(4)Contourlet is more appropriate for analyzing the image edges such as curve or linear characteristics than wavelet transform, and it has better approximation precision and sparsity description. In this paper, the second generation Contourlet transform theory and property are researched, and the image fusion method based on the second generation Contourlet transform is proposed, the panchromatic image and multi-spectral images are decomposed using Contourlet transform, then the Contourlet coefficients are fused with the fusion regular in the corresponding scales, and finally the fused coefficients are reconstructed to obtain fusion images, the image rule of self-adaptive was proposed,and which would select coefficients auto-adapted,which solved the question simultaneously.Remote sensing images are taken as experimental data, and the experimental results show the effectiveness of the method.
引文
[1]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社,2003,8.
[2]G.Simone,A.Farina.Image fusion techniques for remote sensing applications[J].Information Fusion.2002(3):3-15.
[3]吴连喜.多源遥感数据融合与评价[M].南昌:江西科学技术出版社,2003.6.
[4]朱俊杰.高分辨率光学和SAR遥感数据融合及典型目标提取方法研究[D].北京:中国科学院遥感应用研究所,2005.
[5]钟志勇,陈鹰.多源信息融合中小波变换的应用研究[J].测绘学报.2002,5(31):56-60.
[6]翁永玲,田庆永.遥感数据融合方法分析与评价综述[J].遥感信息.2003,3:49-54.
[7]樊旭艳,尹连旺,付春龙等.QuickBird遥感影像数据融合方法研究[J].装备指挥技术学院学报.2006(6),17(3):81-85.
[8]贾永红,李德仁,孙家柄.多源遥感影像数据融合[J].遥感技术与应用[J].2000,15(1):41-44.
[9]王洪华,王双亭,杜春萍.基于多进制小波的多源遥感影像融合[J].中国图象图形学报.2002,4.7A(4):341-345.
[10]王智军,李德仁,李清泉.利用小波变换对影像进行融合的研究[J].武汉测绘科技大学学报,2000,25(2):137-141.
[11]曹闻,张勇.基于小波包变换与IHS变换的遥感图像融合[J].测绘学院学报.2004(6),21(2):114-117.
[12]Varshney P K.Multi-sensor data fusion.Electronics and Communication Engineering Journal,1997,9(12):245-253.
[13]P.Greenway.The SKIDS data fusion project[J].Sensor Fusion Ⅳ,Proceedinges of SPIE.1992,1611:504-515.
[14]瞿继双,王超,王正志.基于数据融合的遥感图像处理技术[J].中国图像图形学报.2002,7A(10):985-993.
[15]Schistad A H,Jain A K.Multisource classification of remotely sensed data:fusion of landsat TM and SAR images[J].IEEE Transactions on Geoscience and Remote Sensing.1994,32(4):768-778.
[16]贾永红,李德仁,孙家柄.多源遥感影像数据融合[J].烟杆技术与应用.2000,15(1):41-44.
[17]Daily M.I.,Farr T.,Elachi C.Geologic interpretation from composited radar and Landsat imagery[J].Photogrammetric Engineering and Remote Sensing,1979,45(8):1109-1116.
[18]Laner D.T.,Todd W.J.Land cover mapping with merged Landsat RBV and MSS stereoscopic images[C].Proc.of the ASP Fall Technical Conference.1981:680-689.
[19]强赞霞.遥感图像的融合及应用[D].武汉:华中科技大学,2005.
[20]王刚,张志禹.粗糙集结合BP神经网络的数据融合方法研究[J].西安理工大学学报.2006,22(3):311-314.
[21]陈雯,王远飞.基于GA-BP算法的多分辨率遥感影像融合技术[J].遥感技术与应用.2007,22(4):555-559.
[22]武锋强,臧德彦,王建强.数字图像融合研究现状及其评述[J].水利科技与经济.2007,13(1):49-51.
[23]刘哲,任金昌,李言俊.面向遥感应用的图像融合的原理和方法[J].航天计算技术.2001,4:9-12.
[24]李伟.像素级图像融合方法及应用研究[D],广州:华南理工大学,2006.
[25]Pohl C,Van Genderen J L.Multisensor image fusion in remote sensing:concepts,methods and applications[J].International Journal of Remote Sensing.1998,19(5):823-854.
[26]王文君,秦其明,陈思锦等.一种基于特征的遥感影像融合新方法[J].遥感技术与应用.2004,19(4):258-261.
[27]宋杨,万幼川.一种自适应的基于局部小波系数特征的遥感图像融合方法[J].理论研究.2007(1):3-6.
[28]Hall,D.L.,Llinas.J.An introduction to multisensor data fusion[J].Proc.Of the IEEE.1997,85:6-23.
[29]Myungjin Choi.A New Intensity-Hue-Saturation Fusion Approach to Image Fusion With a Tradeoff Paremeter[J].IEEE Transaction on geoscience and remote sensing.2006,44:1672-1682.
[30]Y.Zhang,G.Hong.An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images[J].Information Fusion.2005,6(3):225-234.
[31]P.S.Chavez,Jr.,S.C.Sides,J.A.Andesrson.Comparison of three different methods to merge multiresolution and multispectral data:Landsat TM and SPOT panchromatic[J].Photogramm Eng.Remote Sens.,1991,57(3):295-303.
[32]陆冬华,赵英俊.基于改进型Brovey算法的高光谱数据融合技术[J].世界核地质科学.2006,23(3):177-180.
[33]Jia Y H.Fusion of Landsat TM and SAR image based on principal component analysis[J].Remote Sensing Technology and Application.1998,13(1):4649-4654.
[34]Jin Wu,Jian Liu,Jinwen Tian.Wavelet-based Remote Sensing Image Fusion with PCA and Feature Product[C].Proceeding of the 2006 IEEE International Conference on Mechatronics and Automation.2006,2055-2057.
[35]Toet A,Ruyven L V,Velaton J.Merging thermal and visual images by a contrast pyramid[J].Optical Engineering.1989,28(7):789-792.
[36]邹勤,贾永红.一种基于形态金字塔的遥感影像融合方法及其性能评价[J].武汉大学学报信息科学版.2006,31(11):971-974.
[37]Zhou Y T.Multi-sensor image fusion[J].Proc.of IEEE Int.Conf.on Image Processsing,1994(1):193-197.
[38]于秀兰,钱国蕙,贾晓光.TM和SAR遥感图像特征层融合分类方法的研究[J].高技术通讯.1999(6):32-37.
[39]夏明革,何友,唐小明等.多传感器图像融合综述[J].电光与控制.2002,9(4):1-7.
[40]朱长青,王倩,杨晓梅.基于多进制小波的SPOT全色影像和多光谱遥感影像融合[J].测绘学报.2000,29(2):132-136.
[41]王文君,陈思锦,秦其明等.基于双正交小波的多分辨率遥感图像数据融合[J].现代电子技术.2004,(5):31-34.
[42]Cheng Yinglei,Zhao Rongchun,Hu Fuyuan,eg.A NOVEL ALGORITHM OF MULTI-SENSOR IMAGE FUSION BASED ON WAVELET PACKET TRANSFORM[J].JOURNAL OF ELECTRONICS(CHINA).2006,23(2):314-317.
[43]邢帅,谭兵,徐青等.基于复数小波变换的遥感图像融合新算法[J].武汉大学学报(信息科学版).2007,32(1):75-77.
[44]M.Choi,R.Y.Kim,M.Nam.Fusion of Multispectral and Panchromatic Satellite Images Using the Curvelet Transform[J].IEEE geoscience and remote sensing letters.2005,2(2):136-140.
[45]张强,郭宝龙.一种基于Curvelet变换多传感器图像融合算法[J].光电子·激光.2006,17(9):1123-1127.
[46]F.Nencini,A.Grarzelli,S.Baronti,et al.Remote sensing image fusion using the curvelet transform[J].Information Fusion.2007,(8):143-156.
[47]陈蜜,李德仁,秦前清等.基于Contourlet变换的遥感影像融合算法[J].小型微型计算机系统.2006,27(11):2052-2055.
[48]徐青,张艳,耿则勋等.遥感影像融合与分辨率增强技术[M].北京:科学出版社,2007.
[49]张永生,王仁礼.遥感动态监测[M].北京:解放军出版社,1999.
[50]李军,周月琴,李德仁.小波变换用于高分辨率全色图像与多光谱影像的融合研究[J].遥感学报,1999,3(2):116-120.
[51]王小睿,吴信才,遥感多图像的自动配准方法[J],中国图像图形学报,1997,2(10):735-738.
[52]L.G.Brown.A Survey of Image Registration Techniques[J].ACM Computer Survey 1992,24(4):325-376.
[53]K.A.Kalpoma,J.Kudoh.Image Fusion Processing for IKONOS 1-m Color Imagery[J].IEEE Transactions on geoscience and remote sensing.2007,45(10):3075-3086.
[54]林卉,杜培军,张连蓬.基于小波变换的影像融合算法与效果评价[J].矿业研究与开发,2005,25(2):48-52.
[55]A.M.Eskicioglu,P.S.Fisher.Image quality measures and their performance[J].IEEE Transactions on Communications,1995,43(12):2959-2965.
[56]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[J].光学学报,2002,21(11):1336-1342.
[57]王宏,敬忠良等.基于滤波器组的遥感图像融合方法及其性能分析研究[J].红外与毫米波学报,2004,23(3):164-168.
[58]贾永红,李德仁.SAR与TM影像的IHS变换复合及其质量定量评价[J].国土资源遥感,1997,(3):34-39.
[59]林卉,杜培军.基于小波变换的遥感影像融合与评价[J].计算机应用,2005,(4):6-9.
[60]王海晖,彭嘉雄,吴巍.多源遥感图像融合效果评价方法研究[J].计算机工程与应用,2003,39(25):33-37.
[61]李弼程,魏俊,彭天强.遥感影像融合效果的客观分析与评价[J].计算机工程与科学,2004,26(1):42-46.
[62]韩玲,吴汉宁.像素级多源遥感影像信息融合的客观分析与质量评价[J].应用技术.2005,5:40-44.
[63]王文杰,唐娉,朱重光.一种基于小波变换的图像融合算法[J].中国图像图形学报 A,2001,6(11):1130-1136.
[64]王红梅,李言俊,张科.一种新的多传感器图像融合方法[J].西北大学学报.2005,23(6):793-797.
[65]李树涛,王耀南,龚理专.多聚焦图像融合中最佳小波分解层数的选取[J].系统工程与电子技术.2002,24(6):45-48.
[66]Xydeas C S,Petrovic V S.Objective.pixel-level image fusion performance measure[J].Proceedings of SPIE.2000,4051:89-98.
[67]阳方林,郭红阳,杨风暴.像素级图像融合效果的评价方法研究[J].测试技术学报.2002,16(4):276-279.
[68]Zhenhua Li,Zhongliang Jing,Xuhong Yang,Shaoyuan Sun.Color transfer based remote sensing image fusion using non-separable wavelet frame transform.Pattern Recognition Letters.2005,(26):2006-2014.
[69]B.srinivasa Reddy,B.N.Chatterji.An FFT-Based Technique for Translation,Rotation,and Scale-Invariant Image Registration.IEEE Transactions on image processing,and Remote Sensing,1996,5(8):1266-1271.
[70]J.Zhou,D.L.Civco,and J.A.Silander.A wavelet transform method to merge Landsat TM and SPOT panchromatic data[J].Int.J.Remote Sens.1998,19(4):743-757.
[71]刘坤.像素级多传感器图像融合的研究[D].西安:西北工业大学,2007.
[72]赵亮红.基于小波变换的图像融合研究[D].成都:成都理工大学,2006.
[73]J.J.Lewis,R.J.O'Callaghan,and S.G.Nikolov,et al.Region-based Image Fusion Using Complex Wavelet[C].Proceedings of the 7~(th) International Conference on Information Fusion(Fusion 2004),International Society of Information Fusion(ISIF),Stockholm,Sweden,2004,6:555-562.
[74]刘哲,任金昌,李言俊.面向遥感应用的图像融合的原理和方法[J].航天计算技术.2001,4:9-12.
[75]吴艳.多传感器数据融合算法研究[D].西安电子科技大学博士学位论文,2003,4.
[76]申晓华.基于区域能量的图像融合[D].河南:河南大学,2007.
[77]刘坤.基于Contourlet变换的区域特征自适应图像融合算法[J].光学学报,.2008,4:682-686
[78]M.N.Do,M.Vetterli.Contourlets[A].J Stoeckler,G V Welland.Beyond Wavelets[C].Academic Press,New York,2002.
[79]M.N.Do.Directional Multiresolution Image Representations[D].Department of communication systems,Swiss Federal institute of Technology Lausanne,Switzerland,2001.
[80]戴维,于盛林,孙栓.基于Contourlet变换自适应阈值的图像去噪算法[J].电子学报,2007,35(10):1939-1943.
[81]李光鑫,王珂.基于Contourlet变换的彩色图像融合算法[J].电子学报,2007,35(1):112-117.
[82]李晖晖,郭雷,刘航.基于Curvelet变换的图像融合研究[J].光学学报.2006,26(5):657-662.
[83]张强,郭宝龙.应用第Curvelet变换的遥感图像融合[J].光学 精密工程.2007,15(7):1130-1136.
[84]李晖晖.多传感器图像融合算法研究[D].西北工业大学博士学位论文,2006,4.
[2]G.Simone,A.Farina.Image fusion techniques for remote sensing applications[J].Information Fusion.2002(3):3-15.
[3]吴连喜.多源遥感数据融合与评价[M].南昌:江西科学技术出版社,2003.6.
[4]朱俊杰.高分辨率光学和SAR遥感数据融合及典型目标提取方法研究[D].北京:中国科学院遥感应用研究所,2005.
[5]钟志勇,陈鹰.多源信息融合中小波变换的应用研究[J].测绘学报.2002,5(31):56-60.
[6]翁永玲,田庆永.遥感数据融合方法分析与评价综述[J].遥感信息.2003,3:49-54.
[7]樊旭艳,尹连旺,付春龙等.QuickBird遥感影像数据融合方法研究[J].装备指挥技术学院学报.2006(6),17(3):81-85.
[8]贾永红,李德仁,孙家柄.多源遥感影像数据融合[J].遥感技术与应用[J].2000,15(1):41-44.
[9]王洪华,王双亭,杜春萍.基于多进制小波的多源遥感影像融合[J].中国图象图形学报.2002,4.7A(4):341-345.
[10]王智军,李德仁,李清泉.利用小波变换对影像进行融合的研究[J].武汉测绘科技大学学报,2000,25(2):137-141.
[11]曹闻,张勇.基于小波包变换与IHS变换的遥感图像融合[J].测绘学院学报.2004(6),21(2):114-117.
[12]Varshney P K.Multi-sensor data fusion.Electronics and Communication Engineering Journal,1997,9(12):245-253.
[13]P.Greenway.The SKIDS data fusion project[J].Sensor Fusion Ⅳ,Proceedinges of SPIE.1992,1611:504-515.
[14]瞿继双,王超,王正志.基于数据融合的遥感图像处理技术[J].中国图像图形学报.2002,7A(10):985-993.
[15]Schistad A H,Jain A K.Multisource classification of remotely sensed data:fusion of landsat TM and SAR images[J].IEEE Transactions on Geoscience and Remote Sensing.1994,32(4):768-778.
[16]贾永红,李德仁,孙家柄.多源遥感影像数据融合[J].烟杆技术与应用.2000,15(1):41-44.
[17]Daily M.I.,Farr T.,Elachi C.Geologic interpretation from composited radar and Landsat imagery[J].Photogrammetric Engineering and Remote Sensing,1979,45(8):1109-1116.
[18]Laner D.T.,Todd W.J.Land cover mapping with merged Landsat RBV and MSS stereoscopic images[C].Proc.of the ASP Fall Technical Conference.1981:680-689.
[19]强赞霞.遥感图像的融合及应用[D].武汉:华中科技大学,2005.
[20]王刚,张志禹.粗糙集结合BP神经网络的数据融合方法研究[J].西安理工大学学报.2006,22(3):311-314.
[21]陈雯,王远飞.基于GA-BP算法的多分辨率遥感影像融合技术[J].遥感技术与应用.2007,22(4):555-559.
[22]武锋强,臧德彦,王建强.数字图像融合研究现状及其评述[J].水利科技与经济.2007,13(1):49-51.
[23]刘哲,任金昌,李言俊.面向遥感应用的图像融合的原理和方法[J].航天计算技术.2001,4:9-12.
[24]李伟.像素级图像融合方法及应用研究[D],广州:华南理工大学,2006.
[25]Pohl C,Van Genderen J L.Multisensor image fusion in remote sensing:concepts,methods and applications[J].International Journal of Remote Sensing.1998,19(5):823-854.
[26]王文君,秦其明,陈思锦等.一种基于特征的遥感影像融合新方法[J].遥感技术与应用.2004,19(4):258-261.
[27]宋杨,万幼川.一种自适应的基于局部小波系数特征的遥感图像融合方法[J].理论研究.2007(1):3-6.
[28]Hall,D.L.,Llinas.J.An introduction to multisensor data fusion[J].Proc.Of the IEEE.1997,85:6-23.
[29]Myungjin Choi.A New Intensity-Hue-Saturation Fusion Approach to Image Fusion With a Tradeoff Paremeter[J].IEEE Transaction on geoscience and remote sensing.2006,44:1672-1682.
[30]Y.Zhang,G.Hong.An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images[J].Information Fusion.2005,6(3):225-234.
[31]P.S.Chavez,Jr.,S.C.Sides,J.A.Andesrson.Comparison of three different methods to merge multiresolution and multispectral data:Landsat TM and SPOT panchromatic[J].Photogramm Eng.Remote Sens.,1991,57(3):295-303.
[32]陆冬华,赵英俊.基于改进型Brovey算法的高光谱数据融合技术[J].世界核地质科学.2006,23(3):177-180.
[33]Jia Y H.Fusion of Landsat TM and SAR image based on principal component analysis[J].Remote Sensing Technology and Application.1998,13(1):4649-4654.
[34]Jin Wu,Jian Liu,Jinwen Tian.Wavelet-based Remote Sensing Image Fusion with PCA and Feature Product[C].Proceeding of the 2006 IEEE International Conference on Mechatronics and Automation.2006,2055-2057.
[35]Toet A,Ruyven L V,Velaton J.Merging thermal and visual images by a contrast pyramid[J].Optical Engineering.1989,28(7):789-792.
[36]邹勤,贾永红.一种基于形态金字塔的遥感影像融合方法及其性能评价[J].武汉大学学报信息科学版.2006,31(11):971-974.
[37]Zhou Y T.Multi-sensor image fusion[J].Proc.of IEEE Int.Conf.on Image Processsing,1994(1):193-197.
[38]于秀兰,钱国蕙,贾晓光.TM和SAR遥感图像特征层融合分类方法的研究[J].高技术通讯.1999(6):32-37.
[39]夏明革,何友,唐小明等.多传感器图像融合综述[J].电光与控制.2002,9(4):1-7.
[40]朱长青,王倩,杨晓梅.基于多进制小波的SPOT全色影像和多光谱遥感影像融合[J].测绘学报.2000,29(2):132-136.
[41]王文君,陈思锦,秦其明等.基于双正交小波的多分辨率遥感图像数据融合[J].现代电子技术.2004,(5):31-34.
[42]Cheng Yinglei,Zhao Rongchun,Hu Fuyuan,eg.A NOVEL ALGORITHM OF MULTI-SENSOR IMAGE FUSION BASED ON WAVELET PACKET TRANSFORM[J].JOURNAL OF ELECTRONICS(CHINA).2006,23(2):314-317.
[43]邢帅,谭兵,徐青等.基于复数小波变换的遥感图像融合新算法[J].武汉大学学报(信息科学版).2007,32(1):75-77.
[44]M.Choi,R.Y.Kim,M.Nam.Fusion of Multispectral and Panchromatic Satellite Images Using the Curvelet Transform[J].IEEE geoscience and remote sensing letters.2005,2(2):136-140.
[45]张强,郭宝龙.一种基于Curvelet变换多传感器图像融合算法[J].光电子·激光.2006,17(9):1123-1127.
[46]F.Nencini,A.Grarzelli,S.Baronti,et al.Remote sensing image fusion using the curvelet transform[J].Information Fusion.2007,(8):143-156.
[47]陈蜜,李德仁,秦前清等.基于Contourlet变换的遥感影像融合算法[J].小型微型计算机系统.2006,27(11):2052-2055.
[48]徐青,张艳,耿则勋等.遥感影像融合与分辨率增强技术[M].北京:科学出版社,2007.
[49]张永生,王仁礼.遥感动态监测[M].北京:解放军出版社,1999.
[50]李军,周月琴,李德仁.小波变换用于高分辨率全色图像与多光谱影像的融合研究[J].遥感学报,1999,3(2):116-120.
[51]王小睿,吴信才,遥感多图像的自动配准方法[J],中国图像图形学报,1997,2(10):735-738.
[52]L.G.Brown.A Survey of Image Registration Techniques[J].ACM Computer Survey 1992,24(4):325-376.
[53]K.A.Kalpoma,J.Kudoh.Image Fusion Processing for IKONOS 1-m Color Imagery[J].IEEE Transactions on geoscience and remote sensing.2007,45(10):3075-3086.
[54]林卉,杜培军,张连蓬.基于小波变换的影像融合算法与效果评价[J].矿业研究与开发,2005,25(2):48-52.
[55]A.M.Eskicioglu,P.S.Fisher.Image quality measures and their performance[J].IEEE Transactions on Communications,1995,43(12):2959-2965.
[56]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[J].光学学报,2002,21(11):1336-1342.
[57]王宏,敬忠良等.基于滤波器组的遥感图像融合方法及其性能分析研究[J].红外与毫米波学报,2004,23(3):164-168.
[58]贾永红,李德仁.SAR与TM影像的IHS变换复合及其质量定量评价[J].国土资源遥感,1997,(3):34-39.
[59]林卉,杜培军.基于小波变换的遥感影像融合与评价[J].计算机应用,2005,(4):6-9.
[60]王海晖,彭嘉雄,吴巍.多源遥感图像融合效果评价方法研究[J].计算机工程与应用,2003,39(25):33-37.
[61]李弼程,魏俊,彭天强.遥感影像融合效果的客观分析与评价[J].计算机工程与科学,2004,26(1):42-46.
[62]韩玲,吴汉宁.像素级多源遥感影像信息融合的客观分析与质量评价[J].应用技术.2005,5:40-44.
[63]王文杰,唐娉,朱重光.一种基于小波变换的图像融合算法[J].中国图像图形学报 A,2001,6(11):1130-1136.
[64]王红梅,李言俊,张科.一种新的多传感器图像融合方法[J].西北大学学报.2005,23(6):793-797.
[65]李树涛,王耀南,龚理专.多聚焦图像融合中最佳小波分解层数的选取[J].系统工程与电子技术.2002,24(6):45-48.
[66]Xydeas C S,Petrovic V S.Objective.pixel-level image fusion performance measure[J].Proceedings of SPIE.2000,4051:89-98.
[67]阳方林,郭红阳,杨风暴.像素级图像融合效果的评价方法研究[J].测试技术学报.2002,16(4):276-279.
[68]Zhenhua Li,Zhongliang Jing,Xuhong Yang,Shaoyuan Sun.Color transfer based remote sensing image fusion using non-separable wavelet frame transform.Pattern Recognition Letters.2005,(26):2006-2014.
[69]B.srinivasa Reddy,B.N.Chatterji.An FFT-Based Technique for Translation,Rotation,and Scale-Invariant Image Registration.IEEE Transactions on image processing,and Remote Sensing,1996,5(8):1266-1271.
[70]J.Zhou,D.L.Civco,and J.A.Silander.A wavelet transform method to merge Landsat TM and SPOT panchromatic data[J].Int.J.Remote Sens.1998,19(4):743-757.
[71]刘坤.像素级多传感器图像融合的研究[D].西安:西北工业大学,2007.
[72]赵亮红.基于小波变换的图像融合研究[D].成都:成都理工大学,2006.
[73]J.J.Lewis,R.J.O'Callaghan,and S.G.Nikolov,et al.Region-based Image Fusion Using Complex Wavelet[C].Proceedings of the 7~(th) International Conference on Information Fusion(Fusion 2004),International Society of Information Fusion(ISIF),Stockholm,Sweden,2004,6:555-562.
[74]刘哲,任金昌,李言俊.面向遥感应用的图像融合的原理和方法[J].航天计算技术.2001,4:9-12.
[75]吴艳.多传感器数据融合算法研究[D].西安电子科技大学博士学位论文,2003,4.
[76]申晓华.基于区域能量的图像融合[D].河南:河南大学,2007.
[77]刘坤.基于Contourlet变换的区域特征自适应图像融合算法[J].光学学报,.2008,4:682-686
[78]M.N.Do,M.Vetterli.Contourlets[A].J Stoeckler,G V Welland.Beyond Wavelets[C].Academic Press,New York,2002.
[79]M.N.Do.Directional Multiresolution Image Representations[D].Department of communication systems,Swiss Federal institute of Technology Lausanne,Switzerland,2001.
[80]戴维,于盛林,孙栓.基于Contourlet变换自适应阈值的图像去噪算法[J].电子学报,2007,35(10):1939-1943.
[81]李光鑫,王珂.基于Contourlet变换的彩色图像融合算法[J].电子学报,2007,35(1):112-117.
[82]李晖晖,郭雷,刘航.基于Curvelet变换的图像融合研究[J].光学学报.2006,26(5):657-662.
[83]张强,郭宝龙.应用第Curvelet变换的遥感图像融合[J].光学 精密工程.2007,15(7):1130-1136.
[84]李晖晖.多传感器图像融合算法研究[D].西北工业大学博士学位论文,2006,4.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |