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Mixed-Pixel Decomposition of SAR Images Based on Single-Pixel ICA with Selective Members

机译:基于选择性成员的单像素ICA的SAR图像混合像素分解

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摘要

In the decomposition of synthetic aperture radar (SAR) images with mixed pixels, two issues cannot be avoided; (1) there are more land cover types than the number of SAR image channels; and (2) the fixity of the land cover types impacts the precision of the decomposition. Based on the idea that varying the land cover type according to changes in pixels will lead to an improvement in decomposition accuracy, we propose the SM-SPICA (single-pixel Independent Component Analysis with selective members) algorithm that adjusts the land cover type dynamically. The algorithm is further based on mixed-pixel decomposition in a linear-spectrum mixed model and the relevant ICA theory. Experimental results using ENVISAT-ASAR images (both VV and VH) of Beijing confirm that SM-SPICA can decompose SAR images containing more land cover types than the number of image channels with greater accuracy.
机译:在分解具有混合像素的合成孔径雷达(SAR)图像时,无法避免两个问题。 (1)土地覆盖类型比SAR图像通道的数量更多; (2)土地覆盖类型的固定性影响分解的精度。基于根据像素变化来改变土地覆盖类型会提高分解精度的想法,我们提出了SM-SPICA(具有选择性成员的单像素独立分量分析)算法,该算法可动态调整土地覆盖类型。该算法进一步基于线性光谱混合模型中的混合像素分解以及相关的ICA理论。使用北京的ENVISAT-ASAR图像(VV和VH两者)进行的实验结果证实,SM-SPICA可以比包含更多图像通道数量的土地覆盖类型更多的SAR图像进行分解。

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  • 来源
    《GIScience & remote sensing》 |2011年第1期|p.130-140|共11页
  • 作者单位

    College of Information Science and Technology, Beijing Normal University, Beijing 100875, China;

    College of Information Science and Technology, Beijing Normal University, Beijing 100875, China;

    College of Information Science and Technology, Beijing Normal University, Beijing 100875, China;

    College of Information Science and Technology, Beijing Normal University, Beijing 100875, China;

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