多光谱和SAR图像的分析

Shuchun Zhang, Yun Zhang, Yongbin Chou, Ziheng Wang, Yifu Shi, Zhenyu Sun
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引用次数: 0

摘要

SAR图像和多光谱图像都可用于动态监测、矿产资源调查、城乡监测与评价、交通网络勘探、森林资源调查、荒漠化监测等。本文讨论了多光谱与SAR图像融合提高分类质量的方法,比较了常用的SAR图像与多光谱图像融合算法,即标准颜色变换(Brovey)方法、相位恢复(Gram-Schmidt)方法和色彩空间变换(HSV)方法、主成分变换超分辨(PCA)方法和偏导(Pansharp)方法,融合后的图像与多光谱和SAR图像更接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the Multispectral and SAR Image
The SAR image and the multispectral image are both used for dynamic monitoring, mineral resources investigation, urban and rural monitoring and evaluation, traffic network exploration, forest resources investigation, desertification monitoring, and so on. The multi-spectral and SAR image fusion to improve the classify quality is discussed in this paper, compared the common fusion algorithms of the SAR image and multi spectral images, that is standard color transform (Brovey) method, phase recovery (Gram-Schmidt) method and color space transform (HSV) method, principal component transformation super resolution (PCA) method and Bias method (Pansharp), by which the fused image is more relative with the multi-spectral and SAR.
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