SAR Image Change Detection Based on Multi-scale Feature Extraction

Xiao-Hong Yuan, Chao Chen, Shan Tian, Jiandan Zhong
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Abstract

In order to improve the contrast of the difference image and reduce the interference of the speckle noise in the synthetic aperture radar (SAR) image, this paper proposes a SAR image change detection algorithm based on multi-scale feature extraction. In this paper, a kernel matrix with weights is used to extract features of two original images, and then the logarithmic ratio method is used to obtain the difference images of two images, and the change area of the images are extracted. Then, the different sizes of kernel matrix are used to extract the abstract features of different scales of the difference image. This operation can make the difference image have a higher contrast. Finally, the cumulative weighted average is obtained to obtain the final difference image, which can further suppress the speckle noise in the image.
基于多尺度特征提取的SAR图像变化检测
为了提高差分图像的对比度,降低SAR图像中散斑噪声的干扰,本文提出了一种基于多尺度特征提取的SAR图像变化检测算法。本文采用带权重的核矩阵对两幅原始图像进行特征提取,然后采用对数比值法得到两幅图像的差值图像,提取图像的变化面积。然后,利用不同大小的核矩阵提取差分图像的不同尺度的抽象特征。这种操作可以使差值图像具有更高的对比度。最后进行累积加权平均,得到最终的差分图像,进一步抑制图像中的散斑噪声。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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