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A novel super-resolution method of PolSAR images based on target decomposition and polarimetric spatial correlation

机译:基于目标分解和极化空间相关的PolSAR图像超分辨率新方法

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The polarimetric synthetic aperture radar (PolSAR) is becoming more and more popular in remote-sensing research areas. However, due to system limitations, such as bandwidth of the signal and the physical dimension of antennas, the resolution of PolSAR images cannot be compared with those of optical remote-sensing images. Super-resolution processing of PolSAR images 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 within one resolution cell, details of the images can be enhanced, which that means the resolution of the images is improved. In this article, a novel super-resolution algorithm for PolSAR images is proposed, in which polarimetric target decomposition and polarimetric spatial correlation are both taken into consideration. The super-resolution method, based on polarimetric spatial correlation (SRPSC), can make full use of the polarimetric spatial correlation to allocate different scattering mechanisms of PolSAR images. The advantage of SRPSC is that the phase information can be preserved in the processed PolSAR images. The proposed methods are demonstrated with the German Aerospace Center (DLR) Experimental SAR (E-SAR) L-band full polarized images of the Oberpfaffenhofen Test Site Area in Germany, obtained on 30 September 2000. The experimental results of the SRPSC confirms the effectiveness of the proposed methods.1 View full textDownload full textRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/01431161.2010.492251
机译:极化合成孔径雷达(PolSAR)在遥感研究领域越来越受欢迎。但是,由于系统的局限性,例如信号的带宽和天线的物理尺寸,PolSAR图像的分辨率无法与光学遥感图像的分辨率进行比较。对于PolSAR图像应用程序,例如图像解释和目标检测,通常需要对PolSAR图像进行超分辨率处理。通常,在PolSAR图像中,每个分辨率都包含几种不同的散射机制。如果可以将这些机制分配给一个分辨率单元中的不同部分,则可以增强图像的细节,这意味着可以提高图像的分辨率。本文提出了一种新的PolSAR图像超分辨率算法,该算法同时考虑了极化目标分解和极化空间相关性。基于极化空间相关性(SRPSC)的超分辨率方法可以充分利用极化空间相关性来分配PolSAR图像的不同散射机制。 SRPSC的优点是可以将相位信息保留在已处理的PolSAR图像中。 2000年9月30日获得的德国Oberpfaffenhofen试验场区域的德国航空航天中心(DLR)实验性SAR(E-SAR)L波段全偏振图像证明了所提出的方法。SRPSC的实验结果证实了其有效性。 1 查看全文下载全文相关的变量addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,service_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon, digg,google,more“,发布号:” ra-4dff56cd6bb1830b“};添加到候选列表链接永久链接http://dx.doi.org/10.1080/01431161.2010.492251

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