Comparison of diffirent fusion methods and their performance evaluation to high spatial resolution remote sensing data of GF

doi:10.13474/j.cnki.11-2246.2019.0174

Abstract

Abstract:

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.

Key words: GaoFen-1(GF-1), image fusion, quality assessment, remote sensing

CLC Number:

P237

SHAO Yakui, ZHU Changming, ZHANG Xin, SHEN Qian. Comparison of diffirent fusion methods and their performance evaluation to high spatial resolution remote sensing data of GF[J]. 测绘通报, 2019, 0(6): 5-10.

References

[1] 赵展,卢莹,夏旺,等.利用融合方法提升WorldView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 pan-sharpening[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.Twenty-five 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.