基于目标分解和极化空间相关的极化SAR图像超分辨率研究

B. Zou, Hui-cheng Hao, Xingjie Guo
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引用次数: 9

摘要

极化合成孔径雷达(PolSAR)在遥感研究领域得到越来越广泛的应用。PolSAR图像的超分辨率处理通常用于图像解译和目标检测等领域。通常在PolSAR图像中,每个分辨率包含几种不同的散射机制。如果可以将这些机制分配到一个分辨率单元中的不同部分,则可以增强图像的细节,从而提高图像的分辨率。本文提出了一种考虑目标分解和极化空间相关的PolSAR图像超分辨处理新算法。ESAR l波段全偏振图像的实验结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Super-Resolution of Polarimetric SAR Images Based on Target Decomposition and Polarimetric Spatial Correlation
Polarimetric SAR (PolSAR) is becoming more and more popular in remote sensing research area. Super-resolution processing of PolSAR image is usually desired for PolSAR image applications, such as image interpretation and target detection. Usually in a PolSAR image, each resolution contains several different scattering mechanisms. If these mechanisms can be allocated to different parts in one resolution cell, the details of the images can be enhanced, which means the resolution of the images is improved. In this paper, a new super-resolution algorithm for PolSAR image processing is proposed, in which target decomposition and polarimetric spatial correlation are both taken into consideration. Results of ESAR L-band full polarized images have validated the effectiveness of the proposed method.
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