国产高分卫星遥感影像融合方法比较与评价
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摘要
选择适宜的融合方法有利于卫星遥感影像融合产品更好地服务于生产实践及科学研究。本文在总结现有影像像素级融合算法原理的基础上,选用Pansharp、Gram-Schmidt、HPF、Ehlers、Subtractive、Modified IHS、Brovey、PCA、NNDiffuse等多种常用的影像融合方法对国产高分影像的全色和多光谱数据进行了融合处理,并从定性和定量的角度对融合结果进行了详细评价,试图寻找适用于国产高分卫星遥感影像的最佳融合方法。结果表明:针对国产高分一号卫星遥感数据,超分辨率贝叶斯算法融合效果在视觉效果与影像质量定量评价指标中综合表现最佳; Gram-Schmidt、NNDiffuse、Subtractive和HPF融合结果地物边界最为清晰; Modified IHS、PCA、Brovey融合影像色彩失真较为明显; NNDiffuse在可见光波段表现较突出; Gram-Schmidt在近红外波段表现效果最佳。
Choosing an appropriate fusion method is conducive to better serving the practice and scientific research of remote sensing image. This paper tries to find the best fusion method for high resolution remote sensing images of China satellite at the basis of summarizing the existing image pixel-level fusion algorithms. Pansharp,Gram-Schmidt,HPF,Ehlers,Subtractive,Modified IHS transform,Brovey,PCA,NND and etc. methods were selected to fuse the panchromatic and multispectral data of high-resolution images of China satellites,and then 9 fusion results were evaluated qualitatively and quantitatively. The results show that Pansharping algorithm are the best both in the visual effect and the quantitative indicators of image quality evaluation. The results of Gram-Schmidt,NNDiffuse,Subtractive and HPF have the clearest boundary. Moreover,the result of Modified IHS,PCA and Brovey have obvious color distortion. The result of NND is more prominent in the visible band and Gram-Schmidt performs best in near infrared band. The information presented in this paper can provide technical reference for the application and research of GF-1 satellite data in the future.
Choosing an appropriate fusion method is conducive to better serving the practice and scientific research of remote sensing image. This paper tries to find the best fusion method for high resolution remote sensing images of China satellite at the basis of summarizing the existing image pixel-level fusion algorithms. Pansharp,Gram-Schmidt,HPF,Ehlers,Subtractive,Modified IHS transform,Brovey,PCA,NND and etc. methods were selected to fuse the panchromatic and multispectral data of high-resolution images of China satellites,and then 9 fusion results were evaluated qualitatively and quantitatively. The results show that Pansharping algorithm are the best both in the visual effect and the quantitative indicators of image quality evaluation. The results of Gram-Schmidt,NNDiffuse,Subtractive and HPF have the clearest boundary. Moreover,the result of Modified IHS,PCA and Brovey have obvious color distortion. The result of NND is more prominent in the visible band and Gram-Schmidt performs best in near infrared band. The information presented in this paper can provide technical reference for the application and research of GF-1 satellite data in the future.
引文
[1]赵展,卢莹,夏旺,等.利用融合方法提升World View短波红外影像分辨率[J].测绘通报,2017(12):16-20.
[2]黄波,赵涌泉.多源卫星遥感影像时空融合研究的现状及展望[J].测绘学报,2017,46(10):1492-1499.
[3]王海晖,彭嘉雄,吴巍.基于小波包变换的遥感图像融合[J].中国图象图形学报,2002,7(9):932-937.
[4] ZHANG Y. A new automatic approach for effectively fusing Landsat 7 as well as IKONOS images[C]∥IEEE International Geoscience&Remote Sensing Symposium.Toronto:IEEE,2002.
[5] LABEN C A,BROWER B V. Process for enhancing the spatial resolution of multispectral imagery using pansharpening[R].[S. l.]:Eastman Kodak Company,2000.
[6] SCHOWENGERDT R A. Reconstruction of multispatial,multispectral image data using spatial frequency content[J]. Photogrammetric Engineering&Remote Sensing,1980,46(10):1325-1334.
[7] EHLERS M. Multisensor image fusion techniques in remote sensing[J]. Isprs Journal of Photogrammetry&Remote Sensing,1991,46(1):19-30.
[8] ASHRAF S,BRABYN L,HICHS B J. Image data fusion for the remote sensing of freshwater environments[J].Applied Geography,2012,32(2):619-628.
[9] SIDDIQUI Y. The modified IHS method for fusing satellite imagery[C]∥Proceedings of the ASPRS 2003 An nual Conference. Alaska:[s.n.],2003.
[10] GILLESPIE A R. Color enhancement of highly correlated images II. Channel ratio and ‘chromaticity’transformation techniques[J]. Remote Sensing of Environment,1987,22(3):343-365.
[11] CHAVEZ P S,SIDES S C,ANDERSON J A. Comparison of three different methods to merge multiresolution and multispectral data:landsat TM and SPOT panchromatic[J]. Photogrammetric Engineering&Remote Sensing,1991,57(3):295-303.
[12] SUN W,CHEN B,MESSINGER D W. Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[J]. Optical Engineering, 2014, 53(1):013107.
[13]李霖,佘梦媛,罗恒. ZY-3卫星全色与多光谱影像融合方法比较[J].农业工程学报,2014,30(16):157-165.
[14]吴满意,付冬暇,王占宏,等.资源三号卫星影像融合优化方法探讨[J].测绘科学,2016,41(6):108-112.
[15]江威,何国金,倪愿,等.高分二号卫星影像融合方法与效果评价[J].科学技术与工程,2017,17(15):120-125.
[16]黄鹤,冯毅,张萌,等.天绘一号卫星影像的融合及评价研究[J].测绘通报,2013(1):6-9.
[17] VIVONE G,ALPARONE L,CHANUSSOT J,et al. A critical comparison among pansharpening algorithms[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(5):2565-2586.
[18] AIAZZI B,ALPARONE L,BARONTI S,et al.Twentyfive years of pansharpening:a critical review and new developments[M]. 2nd ed. FL:CRC Press,2012:533-548.
[19] SHI W,ZHU C Q,TIAN Y,et al. Wavelet-based image fusion and quality assessment[J]. International Journal of Applied Earth Observations&Geoinformation,2005(6):241-251.
[2]黄波,赵涌泉.多源卫星遥感影像时空融合研究的现状及展望[J].测绘学报,2017,46(10):1492-1499.
[3]王海晖,彭嘉雄,吴巍.基于小波包变换的遥感图像融合[J].中国图象图形学报,2002,7(9):932-937.
[4] ZHANG Y. A new automatic approach for effectively fusing Landsat 7 as well as IKONOS images[C]∥IEEE International Geoscience&Remote Sensing Symposium.Toronto:IEEE,2002.
[5] LABEN C A,BROWER B V. Process for enhancing the spatial resolution of multispectral imagery using pansharpening[R].[S. l.]:Eastman Kodak Company,2000.
[6] SCHOWENGERDT R A. Reconstruction of multispatial,multispectral image data using spatial frequency content[J]. Photogrammetric Engineering&Remote Sensing,1980,46(10):1325-1334.
[7] EHLERS M. Multisensor image fusion techniques in remote sensing[J]. Isprs Journal of Photogrammetry&Remote Sensing,1991,46(1):19-30.
[8] ASHRAF S,BRABYN L,HICHS B J. Image data fusion for the remote sensing of freshwater environments[J].Applied Geography,2012,32(2):619-628.
[9] SIDDIQUI Y. The modified IHS method for fusing satellite imagery[C]∥Proceedings of the ASPRS 2003 An nual Conference. Alaska:[s.n.],2003.
[10] GILLESPIE A R. Color enhancement of highly correlated images II. Channel ratio and ‘chromaticity’transformation techniques[J]. Remote Sensing of Environment,1987,22(3):343-365.
[11] CHAVEZ P S,SIDES S C,ANDERSON J A. Comparison of three different methods to merge multiresolution and multispectral data:landsat TM and SPOT panchromatic[J]. Photogrammetric Engineering&Remote Sensing,1991,57(3):295-303.
[12] SUN W,CHEN B,MESSINGER D W. Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[J]. Optical Engineering, 2014, 53(1):013107.
[13]李霖,佘梦媛,罗恒. ZY-3卫星全色与多光谱影像融合方法比较[J].农业工程学报,2014,30(16):157-165.
[14]吴满意,付冬暇,王占宏,等.资源三号卫星影像融合优化方法探讨[J].测绘科学,2016,41(6):108-112.
[15]江威,何国金,倪愿,等.高分二号卫星影像融合方法与效果评价[J].科学技术与工程,2017,17(15):120-125.
[16]黄鹤,冯毅,张萌,等.天绘一号卫星影像的融合及评价研究[J].测绘通报,2013(1):6-9.
[17] VIVONE G,ALPARONE L,CHANUSSOT J,et al. A critical comparison among pansharpening algorithms[J].IEEE Transactions on Geoscience and Remote Sensing,2015,53(5):2565-2586.
[18] AIAZZI B,ALPARONE L,BARONTI S,et al.Twentyfive years of pansharpening:a critical review and new developments[M]. 2nd ed. FL:CRC Press,2012:533-548.
[19] SHI W,ZHU C Q,TIAN Y,et al. Wavelet-based image fusion and quality assessment[J]. International Journal of Applied Earth Observations&Geoinformation,2005(6):241-251.
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