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Super-Resolution of Polarimetric SAR Images Based on Target Decomposition and Polarimetric Spatial Correlation

机译:基于目标分解和极化空间相关性的极化SAR图像超分辨率

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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.
机译:Polarimetric SAR(POLSAR)在遥感研究区域变得越来越受欢迎。 Polsar图像的超分辨率处理通常需要POLSAR图像应用,例如图像解释和目标检测。通常在POLSAR图像中,每个分辨率包含几种不同的散射机制。如果可以在一个分辨率单元中分配给不同部分的这些机制,则可以增强图像的细节,这意味着改善了图像的分辨率。在本文中,提出了一种新的多分辨率算法,用于多分辨率的PolSAR图像处理算法,其中考虑到目标分解和偏振空间相关。 ESAR L波段完全偏振图像的结果已验证了该方法的有效性。

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