面向地质应用的高分二号卫星影像融合方法评价
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摘要
为了探讨不同影像融合方法在地质应用上的适用性,以高分二号(GF-2)影像为数据源,采用彩色标准化变换(Brovey)、超球体色彩空间变换(HCS)、相位恢复(Gram-Schmidt)、最邻近扩散(NNDiffuse)和高通滤波变换(HPF)等5种融合方法对全色和多光谱数据进行融合实验,并对融合结果进行质量评价。首先从定性和定量两方面进行评价,然后对融合影像进行岩性分类。结果表明:HPF和Gram-Schmidt方法无论是在定性、定量还是岩性分类应用上均具有较好的效果,NNDiffuse和HCS方法融合效果适中,Brovey方法色彩失真明显,该结论可为地质部门提高GF-2卫星的适用性以及对国产卫星数据的推广应用提供参考。
To discuss the applicability of different image fusion methods applied in geology,five fusion methods,Brovey,HCS,Gram-Schmidt,NNDiffuse and HPF transform,are adopted to fuse the panchromatic and multispectral images of GF-2. In order to assess the quality of the fused images,the results were examined through subjective evaluation and quantitative analysis,and then conduct lithological classification for the fused images. The result shows that HPF and Gram-Schmidt transform perform well in all three aspects discussed above. The HCS and NNDiffuse transform have modest performance,and Brovey transform has serious color distortion. This conclusion can provide a good reference for the application of GF-2 images in geological field and promote the popularization of domestic satellite data.
To discuss the applicability of different image fusion methods applied in geology,five fusion methods,Brovey,HCS,Gram-Schmidt,NNDiffuse and HPF transform,are adopted to fuse the panchromatic and multispectral images of GF-2. In order to assess the quality of the fused images,the results were examined through subjective evaluation and quantitative analysis,and then conduct lithological classification for the fused images. The result shows that HPF and Gram-Schmidt transform perform well in all three aspects discussed above. The HCS and NNDiffuse transform have modest performance,and Brovey transform has serious color distortion. This conclusion can provide a good reference for the application of GF-2 images in geological field and promote the popularization of domestic satellite data.
引文
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19 Anandhi D,Valli S. An algorithm for multi-sensor image fusion using maximum a posteriori and nonsubsampled contourlet transform[J]. Computers and Electrical Engineering,2018,65(1):139-152
20 Zhu X L,Eileen H,Gao F,et al. A flexible spatiotemporal method for fusing satellite images with different resolutions[J]. Remote Sensing of Environment,2016,172(1):165-177
21 Amarsaikhan D,Saandar M,Ganzorig M,et al. Comparison of multisource image fusion methods and land cover classification[J]. International Journal of Remote Sensing,2012,33(8):2532-2550
2 胡曼，彭道黎．面向林地分类的GF-2影像融合算法评价[J]．浙江农林大学学报，2017,34(2):340-348Hu Man,Peng Daoli. Comparison of fusion algorithms for GF-2 data from extracted forestland information[J]. Journal of Zhejiang A&F University,2017,34(2):340-348
3 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):108-113Sun Pan,Dong Yusen,Chen Weitao,et al. Research on fusion of GF-2 imagery and quality evaluation[J]. Remote Sensing for Land and Resources,2016,28(4):108-113
4 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):47-51Wang Huabin,Li Guoyuan,Zhang Benkui,et al. Contrast and analysis of different fusion algorithms for ZY-3 satellite images[J]. Science of Surveying and Mapping,2015,40(1):47-51
5 郑中，祁元，张金龙．基于光谱角和光谱距离评价指标的遥感影像融合算法比较研究[J]．遥感技术与应用，2013,28(3):437-443Zheng Zhong,Qi Yuan,Zhang Jinlong. Comparing with different remote sensing image fusion method based on evaluation index of spectral angle and spectral distance:Taking QuickBird data as example[J]. Remote Sensing Technology and Application,2013,28(3):437-443
6 肖昶，余晓敏，韩逸飞．高分二号卫星影像融合技术研究[J]．地理空间信息，2018,16(6):13-16Xiao Chang,Yu Xiaomin,Han Yifei. Research on image fusion technology of GF-2 satellite[J]. Geospatial Information,2018,16(6):13-16
7 Abdikan S,Balik Sanli F,Sunar F,et al. A comparative data-fusion analysis of multi-sensor satellite images[J]. International Journal of Digital Earth,2014,7(8):671-687
8 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):120-125Jiang Wei,He Guojin,Ni Yuan,et al. Evaluation on fusion method for GF-2 satellite PMS image[J]. Science Technology and Engineering,2017,17(15):120-125
9 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):35-40Chen Yepei,Sun Kaimin,Bai Ting,et al. Quality assessment on image fusion methods for GF-2 data[J]. Science of Surveying and Mapping,2017,42(11):35-40
10 周嘉男，艾海滨，张力．高分一号遥感影像融合方法比较研究[J]．地理空间信息，2016,14(2):47-49Zhou Jianan,Ai Haibin,Zhang Li. Comparative study on remote sensing image fusion algorithms for GF-1 satellite images[J]. Geospatial Information,2016,14(2):47-49
11 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):980-986Liu Kun,Fu Jingying,Li Fei. Evaluation study of four fusion methods of GF-1 PAN and multi-spectral images[J]. Remote Sensing Technology and Application,2015,30(5):980-986
12 熊德峰．高分二号卫星影像融合方法探析[J]．测绘与空间地理信息，2016,39(9):102-104Xiong Defeng. Image fusion analysis of the second high-resolution satellite[J]. Geomatics and Spatial Information Technology,2016,39(9):102-104
13 刘川，齐修东，臧文乾，等．基于HIS变换的Gram-Schmidt改进融合算法研究[J]．测绘工程，2018,27(11):9-14Liu Chuan,Qi Xiudong,Zang Wenqian,et al. Research of improved Gram-Schmidt image fusion algorithm based on HIS transform[J]. Engineering of Surveying and Mapping,2018,27(11):9-14
14 薛晶，官云兰，李宜龙，等．高分二号卫星影像融合方法对比和评价[J]．航天返回与遥感，2017,38(2):91-99Xue Jing,Guan Yunlan,Li Yilong,et al. Comparison and evaluation of image fusion algorithms for GF-2 satellite images[J]. Spacecraft Recovery and Remote Sensing,2017,38(2):91-99
15 臧熹．土地工程应用中高分二号卫星影像融合方法的比较研究[J]．土地开发工程研究，2018,3(11):7-12Zang Xi. Comparative study on fusion methods of GF-2 satellite image in land engineering application[J]. Land Development and Engineering Research,2018,3(11):7-12
16 董崧，臧淑英，吴长山，等．SPOT-7遥感图像融合技术对比研究[J]．测绘与空间地理信息，2017,40(1):75-78Dong Song,Zang Shuying,Wu Changshan,et al. Comparison of different image fusion methods using SPOT-7[J]. Geomatics and Spatial Information Technology,2017,40(1):75-78
17 王宇庆．基于局部方差和互信息的融合图像质量评价[J]．光学精密工程，2015,23(10):515-521Wang Yuqing. Fusion image assessment based on local variance and singular value decomposition[J]. Optics and Precision Engineering,2015,23(10):515-521
18 李超，朱满，赵家平．多源遥感影像融合效果的定量评价研究[J]．测绘与空间地理信息，2010,33(3):143-146Li Chao,Zhu Man,Zhao Jiaping. Research of quantitative methods for evaluation of multi-source remote sensing image fusion[J]. Geomatics and Spatial Information Technology,2010,33(3):143-146
19 Anandhi D,Valli S. An algorithm for multi-sensor image fusion using maximum a posteriori and nonsubsampled contourlet transform[J]. Computers and Electrical Engineering,2018,65(1):139-152
20 Zhu X L,Eileen H,Gao F,et al. A flexible spatiotemporal method for fusing satellite images with different resolutions[J]. Remote Sensing of Environment,2016,172(1):165-177
21 Amarsaikhan D,Saandar M,Ganzorig M,et al. Comparison of multisource image fusion methods and land cover classification[J]. International Journal of Remote Sensing,2012,33(8):2532-2550