高景一号影像多方法融合效果评价分析
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摘要
针对我国首个0.5m高分辨率遥感星座高景一号缺少最优融合算法评价的问题,基于ENVI、ERDAS、PCI、ArcGIS四大常用专业软件提供的14种影像分辨率融合方法,开展高景一号影像融合试验,结合目视观察进行主观评价,并选择均值、标准差、信息熵、平均梯度、平均偏差、相关系数等6个统计指标进行客观分析。结果显示,所有的融合方法都能够在提高空间清晰度的同时从总体上保留光谱信息。从遥感人工解译和定量反演2个角度出发,可以考虑选择HPF、Pansharp、Subtractive 3种方法。通过农用地、水体和建筑物3种主要地类的对象提取对比,认为Pansharp融合的结果更为均衡。该文为高景一号影像的深入应用提供参考。
GJ-1 is the first satellite constellation with 0.5 mhigh resolution in China,but lacking of evaluation for best fusion methods.Provided by four commonly used remote sensing softwares which are ENVI,ERDAS,PCI and ArcGIS,14 different image resolution fusion algorithms were used in experiment for merging the images.Combined with the subjective analysis by visual observation,objective evaluation was implemented through six statistical indicators,composed of mean,standard deviation,information entropy,average gradient,average deviation and correlation coefficient.The results show that all the fusion images can preserve the spectral information while improving the spatial resolution.From the perspectives of artificial interpretation and quantitative inversion of remote sensing,HPF,Pansharp and Subtractive can be choosed for working,and the analysis for the effect of object extraction shows Pansharp is likely a more balanced method,which can provide a reference for the GJ-1 application in future.
GJ-1 is the first satellite constellation with 0.5 mhigh resolution in China,but lacking of evaluation for best fusion methods.Provided by four commonly used remote sensing softwares which are ENVI,ERDAS,PCI and ArcGIS,14 different image resolution fusion algorithms were used in experiment for merging the images.Combined with the subjective analysis by visual observation,objective evaluation was implemented through six statistical indicators,composed of mean,standard deviation,information entropy,average gradient,average deviation and correlation coefficient.The results show that all the fusion images can preserve the spectral information while improving the spatial resolution.From the perspectives of artificial interpretation and quantitative inversion of remote sensing,HPF,Pansharp and Subtractive can be choosed for working,and the analysis for the effect of object extraction shows Pansharp is likely a more balanced method,which can provide a reference for the GJ-1 application in future.
引文
[1]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2013.
[2]刘锟,付晶莹,李飞.高分一号卫星4种融合方法评价[J].遥感技术与应用,2015,30(5):980-986.
[3]郭会敏,洪运富,李营,等.基于高分一号卫星影像的多种融合方法比较[J].地理与地理信息科学,2015,31(1):23-26.
[4]王晓绵,姜芸.高分一号遥感卫星影像融合及质量评价方法研究[J].测绘与空间地理信息,2015(8):178-179.
[5]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.
[6]高燕,周成虎,苏奋振,等.天绘一号卫星影像融合及其质量评价[J].地理空间信息,2014,12(2):16-17.
[7]王华斌,李国元,张本奎,等.资源三号卫星影像融合算法对比分析[J].测绘科学,2015,40(1):47-51.
[8]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.
[9]孙攀,董玉森,陈伟涛,等.高分二号卫星影像融合及质量评价[J].国土资源遥感,2016,28(4):108-113.
[10]陈业培,孙开敏,白婷,等.高分二号影像融合方法质量评价[J].测绘科学,2017,42(11):35-40.
[11]TU T,LEE Y,CHANG C,et al.Adjustable intensity-hue-saturation and brovey transform fusion technique for IKONOS/QuickBird imagery[J].Optical Engineering,2005,44(11):116201-116201-10.
[12]VRABEL J C,DORAISWAMY P,MCMURTREY J E,et al.Demonstration of the accuracy of improved-resolution hyperspectral imagery[J].Proc.SPIE 4725,Algorithms and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery VIII,2002,4725(2):556-567.
[13]KLONUS S,EHLERS M.Image fusion using the ehlers spectral characteristics preservation algorithm[J].Giscience&Remote Sensing,2007,44(2):93-116.
[14]邢超.ArcGIS学习指南:ArcToolbox[M].北京:科学出版社,2010.
[15]于海洋,闫柏琨,甘甫平,等.基于Gram Schmidt变换的高光谱遥感图像改进融合方法[J].地理与地理信息科学,2007,23(5):39-42.
[16]PADWICK,C,DESKEVICH,M,PACIFICI,F,et al.WorldView-2Pan-Sharpening[C]∥Conference of American Society for Photogrammetry and Remote Sensing,2010.
[17]吴连喜.一种保持光谱特征的图像融合方法:高通滤波融合法[J].国土资源遥感,2003,15(4):26-29.
[18]SIDDIQUIY.The modified IHS method for fusing satellite imagery[C]∥ASPRS 2003Annual Conference Proceedings,Anchorage:2003.
[19]SUN W,MESSINGER D.Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[J].Optical Engineering,2013,53(1):013107.
[20]ZHANG Y.A new automatic approach for effectively fusing Landsat 7as well as IKONOS images[C]∥Geoscience and Remote Sensing Symposium,2002.IGARSS'02.2002IEEE International.IEEE,2002(4):2429-2431.
[21]WELCHR.Merging Multiresolution SPOT HRV and Landsat TM Data[J].Photogrammetric Engineering&Remote Sensing,1987,53(3):301-303.
[22]党安荣.ERDAS IMAGEINE遥感图像处理教程[M].北京:清华大学出版社,2010.
[23]KING R L,WANG J.A wavelet based algorithm for pan sharpening Landsat 7imagery[C]∥Geoscience and Remote Sensing Symposium,2001.IGARSS'01.IEEE 2001International.IEEE,2001:849-851vol.2.
[24]李鸿洲,王霞,杜建,等.资源三号卫星和SPOT6卫星融合影像对比分析[J].遥感信息,2016,31(1):64-68.
[25]WALT S V D,SCHNBERGER J L,NUNEZIGLESIAS J,et al.Scikit-image:image processing in Python[J].Peerj,2014,2(2):e453.
[26]刘大伟,韩玲,韩晓勇.基于深度学习的高分辨率遥感影像分类研究[J].光学学报,2016(4):298-306.
[2]刘锟,付晶莹,李飞.高分一号卫星4种融合方法评价[J].遥感技术与应用,2015,30(5):980-986.
[3]郭会敏,洪运富,李营,等.基于高分一号卫星影像的多种融合方法比较[J].地理与地理信息科学,2015,31(1):23-26.
[4]王晓绵,姜芸.高分一号遥感卫星影像融合及质量评价方法研究[J].测绘与空间地理信息,2015(8):178-179.
[5]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.
[6]高燕,周成虎,苏奋振,等.天绘一号卫星影像融合及其质量评价[J].地理空间信息,2014,12(2):16-17.
[7]王华斌,李国元,张本奎,等.资源三号卫星影像融合算法对比分析[J].测绘科学,2015,40(1):47-51.
[8]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.
[9]孙攀,董玉森,陈伟涛,等.高分二号卫星影像融合及质量评价[J].国土资源遥感,2016,28(4):108-113.
[10]陈业培,孙开敏,白婷,等.高分二号影像融合方法质量评价[J].测绘科学,2017,42(11):35-40.
[11]TU T,LEE Y,CHANG C,et al.Adjustable intensity-hue-saturation and brovey transform fusion technique for IKONOS/QuickBird imagery[J].Optical Engineering,2005,44(11):116201-116201-10.
[12]VRABEL J C,DORAISWAMY P,MCMURTREY J E,et al.Demonstration of the accuracy of improved-resolution hyperspectral imagery[J].Proc.SPIE 4725,Algorithms and Technologies for Multispectral,Hyperspectral,and Ultraspectral Imagery VIII,2002,4725(2):556-567.
[13]KLONUS S,EHLERS M.Image fusion using the ehlers spectral characteristics preservation algorithm[J].Giscience&Remote Sensing,2007,44(2):93-116.
[14]邢超.ArcGIS学习指南:ArcToolbox[M].北京:科学出版社,2010.
[15]于海洋,闫柏琨,甘甫平,等.基于Gram Schmidt变换的高光谱遥感图像改进融合方法[J].地理与地理信息科学,2007,23(5):39-42.
[16]PADWICK,C,DESKEVICH,M,PACIFICI,F,et al.WorldView-2Pan-Sharpening[C]∥Conference of American Society for Photogrammetry and Remote Sensing,2010.
[17]吴连喜.一种保持光谱特征的图像融合方法:高通滤波融合法[J].国土资源遥感,2003,15(4):26-29.
[18]SIDDIQUIY.The modified IHS method for fusing satellite imagery[C]∥ASPRS 2003Annual Conference Proceedings,Anchorage:2003.
[19]SUN W,MESSINGER D.Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images[J].Optical Engineering,2013,53(1):013107.
[20]ZHANG Y.A new automatic approach for effectively fusing Landsat 7as well as IKONOS images[C]∥Geoscience and Remote Sensing Symposium,2002.IGARSS'02.2002IEEE International.IEEE,2002(4):2429-2431.
[21]WELCHR.Merging Multiresolution SPOT HRV and Landsat TM Data[J].Photogrammetric Engineering&Remote Sensing,1987,53(3):301-303.
[22]党安荣.ERDAS IMAGEINE遥感图像处理教程[M].北京:清华大学出版社,2010.
[23]KING R L,WANG J.A wavelet based algorithm for pan sharpening Landsat 7imagery[C]∥Geoscience and Remote Sensing Symposium,2001.IGARSS'01.IEEE 2001International.IEEE,2001:849-851vol.2.
[24]李鸿洲,王霞,杜建,等.资源三号卫星和SPOT6卫星融合影像对比分析[J].遥感信息,2016,31(1):64-68.
[25]WALT S V D,SCHNBERGER J L,NUNEZIGLESIAS J,et al.Scikit-image:image processing in Python[J].Peerj,2014,2(2):e453.
[26]刘大伟,韩玲,韩晓勇.基于深度学习的高分辨率遥感影像分类研究[J].光学学报,2016(4):298-306.