一种全极化高分SAR与中分光学影像融合方法

doi:10.11978/2016055

热带海洋学报 ›› 2017, Vol. 36 ›› Issue (2): 79-85.doi: 10.11978/2016055cstr: 32234.14.2016055

一种全极化高分SAR与中分光学影像融合方法

万剑华¹(), 臧金霞¹(), 刘善伟¹, 任广波²

1. 中国石油大学(华东)地球科学与技术学院, 山东青岛 266580
2. 国家海洋局第一海洋研究所, 山东青岛 266061

收稿日期:2016-06-03 修回日期:2016-11-07 出版日期:2017-03-20 发布日期:2017-04-06
作者简介:
作者简介：万剑华(1966—), 男, 山东省单县人, 从事3S技术的应用研究。E-mail: wjh66310@163.com
基金资助:
山东省自然科学基金项目(ZR2016DM16);国防科技工业局高分辨率对地观测系统重大专项“海岸带遥感监测与应用示范”;中国石油化工集团科技攻关项目“航测与遥感技术在管线检测中的应用研究”

A fusion method of high-resolution full polarimetric SAR and moderate-resolution optical image

Jianhua WAN¹(), Jinxia ZANG¹(), Shanwei LIU¹, Guangbo REN²

1. School of Geosciences in China University of Petroleum, Qingdao 266580, China
2. The First Institute of Oceanography, State Oceanic Administration, Qingdao 266061, China

Received:2016-06-03 Revised:2016-11-07 Online:2017-03-20 Published:2017-04-06
Supported by:
Natural Science Foundation of Shandong Province of China (ZR2016DM16);Coastal Zone Remote Sensing Monitoring and Application Demonstration of High Resolution Earth Observation System Major Projects;A Application Study on Aerial Survey and Remote Sensing Technology in Detection of Pipeline

摘要/Abstract

摘要：

针对全极化SAR(synthetic aperture radar, 合成孔径雷达)与中分光学影像的融合问题, 提出基于主成分分析(PCA)与HSV(hue, saturation, value, 色调、饱和度、明度)色彩空间变换的遥感影像融合方法。对全极化SAR四个极化波段进行主成分分析, 提取第一主成分, 将中分光学影像变换到HSV空间, 第一主成分替换V分量, 用新的V分量逆变换到RGB空间, 得到全极化SAR与中分光学的融合影像。通过利用Radarsat-2全极化SAR与TM/ETM+中分光学影像开展融合实验, 结果表明, 该方法优于传统融合方法(PCA变换、HSV变换、小波变换等)的单极化SAR与光学影像融合结果, 能够有效利用全极化SAR的纹理信息, 提高影像解译能力。

关键词: 全极化SAR, 中分光学影像, 影像融合, 主成分分析, HSV变换

Abstract:

A method was proposed to solve the fusion problem of full polarimetric synthetic aperture radar (SAR) and moderate-resolution optical remote sensing image, based on principal components analysis (PCA) and HSV transform, where HSV stands for hue, saturation, and value. First, the four bands of full polarization SAR went through principal component analysis, and the first principal component was extracted. Second, moderate-resolution optical image was transformed into the HSV space, and the V component was replaced by the first principal component. Finally, the desired image was obtained by using inverse IHS transform. The experiment was performed using Radarsat-2 full polarimetric SAR and TM/ETM+ moderate-resolution optical image. A comparison of the proposed method with the fusion of single polarimetric SAR and optical image based on a traditional method (PCA transform, HSV transform, or wavelet transform) showed that the proposed method made effective use of the texture information of full polarimetric SAR and improved the capability of image interpretation.

Key words: full polarimetric synthetic aperture radar, moderate-resolution optical image, image fusion, principal component analysis, HSV transformation

中图分类号:

P237

万剑华, 臧金霞, 刘善伟, 任广波. 一种全极化高分SAR与中分光学影像融合方法[J]. 热带海洋学报, 2017, 36(2): 79-85.

Jianhua WAN, Jinxia ZANG, Shanwei LIU, Guangbo REN. A fusion method of high-resolution full polarimetric SAR and moderate-resolution optical image[J]. Journal of Tropical Oceanography, 2017, 36(2): 79-85.

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参考文献 11

1	曹银璇, 燕琴, 赵争, 等, 2007. SAR与光学遥感影像融合在土地资源监测中的应用[J]. 测绘通报, (8): 23-25.
	CAO YINXUAN, YAN QIN, ZHAO ZHENG, et al, 2007. An application of fusing SAR with optical remote sensing in monitoring land resources[J]. Bulletin of Surveying and Mapping, (8): 23-25 (in Chinese).
2	李弼程, 魏俊, 彭天强, 2004. 遥感影象融合效果的客观分析与评价[J]. 计算机工程与科学, 26(1): 42-46.
	LI BICHENG, WEI JUN, PENG TIANQIANG, 2004. Objective analysis and evaluation of remote sensing image fusion effect[J]. Computer Engineering & Science, 26(1): 42-46 (in Chinese).
3	王霄鹏, 张杰, 马毅, 等, 2014. 不同极化方式SAR与TM融合影像滨海湿地分类精度比较[J]. 海洋学研究, 32(1): 40-46.
	WANG XIAOPENG, ZHANG JIE, MA YI, et al, 2014. Comparison of coastal wetland classification accuracy using fused images of different-polarization SAR and TM images[J]. Journal of Marine Sciences, 32(1): 40-46 (in Chinese).
4	翁永玲, 田庆久, 2003. 遥感数据融合方法分析与评价综述[J]. 遥感信息, (3): 49-54.
	WENG YONGLING, TIAN YONGJIU, 2003. Analysis and evaluation of method on remote sensing data fusion[J]. Remote Sensing Information, (3): 49-54 (in Chinese).
5	吴祥, 2013. 极化SAR与可见光遥感影像融合算法研究[D]. 杭州: 杭州电子科技大学: 1-64.
	WU XIANG, 2013. Research on the algorithm of PolSAR and the visible in remote sensing image fusion[D]. Hangzhou: Hangzhou Dianzi University: 1-64 (in Chinese).
6	吴永辉, 计科峰, 郁文贤, 2008. 利用SVM的全极化、双极化与单极化SAR图像分类性能的比较[J]. 遥感学报, 12(1): 46-53.
	WU YONGHUI, JI KEFENG, YU WENXIAN, 2008. Comparison of classification performance of full-, dual- and single-polarization SAR images using SVM[J]. Journal of Remote Sensing, 12(1): 46-53 (in Chinese).
7	徐赣, 尤红建, 2008. 小波的SAR和光学图像融合方法比较研究[J]. 测绘科学, 33(1): 109-112.
	XU GAN, YOU HONGJIAN, 2008. Comparison of image fusion of SAR and optical image based on wavelet transform[J]. Science of Surveying and Mapping, 33(1): 109-112 (in Chinese).
8	张艳宁, 李映, 2014. SAR图像处理的关键技术[M]. 北京: 电子工业出版社: 116-118.
9	ALPARONE L, BARONTI S, GARZELLI A, et al, 2004. Andrea G. Landsat ETM+ and SAR image fusion based on generalized intensity modulation[J]. IEEE Transactions on Geoscience and Remote Sensing, 42(12): 2832-2839.
10	HONG GANG, ZHANG AINING, ZHANG FUQUN, et al, 2014. Integration of optical and synthetic aperture radar (SAR) images to differentiate grassland and alfalfa in Prairie area[J]. International Journal of Applied Earth Observation and Geoinformation, 28: 12-19.
11	RAY S S, 2004. Merging of IRS LISS III and PAN data- evaluation of various methods for a predominantly agricultural area[J]. International Journal of Remote Sensing, 25(13): 2657-2664.

	遥感影像	均值	熵	平均梯度
2009、2010年遥感影像	TM影像	117.891	5.675	16.686
	HH极化	124.750	5.726	16.095
	HV极化	125.578	5.738	14.170
	VH极化	122.281	5.688	14.257
	VV极化	128.422	5.719	13.999
	PCA第一主成分	139.093	5.769	17.792
	本文方法	123.125	5.750	17.241
	PCA变换法	127.000	5.738	14.119
	HSV变换法	129.828	5.813	15.655
2015年遥感影像	ETM+影像	125.516	5.633	13.828
	HH极化	125.141	5.813	16.040
	HV极化	119.656	5.781	16.787
	VH极化	123.375	5.844	15.657
	VV极化	134.936	5.781	14.783
	PCA第一主成分	136.641	5.856	16.836
	本文方法	127.672	5.832	16.166
	PCA变换法	132.156	5.770	15.164
	HSV变换法	142.016	5.847	16.208

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一种全极化高分SAR与中分光学影像融合方法

A fusion method of high-resolution full polarimetric SAR and moderate-resolution optical image

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