SAR图像去噪的分数阶多尺度变分PDE模型及自适应算法
Fractional-order Multi-scale Variation PDE Model and Adaptive Algorithm for SAR Image Denoising
合成孔径雷达(SAR) 图像相干斑噪声抑制中，保持图像的边缘和纹理是非常重要的。首先利用分数阶导数以及负指数Sobolev 空间对图像进行建模，建立了分数阶多尺度变分PDE 模型，然后给出了模型参数自适应选择方法，并在此基础上提出了区域、尺度自适应的SAR 图像去噪算法。数值试验表明，新方法能在有效抑制噪声的同时，能有效地抑制图像的“阶梯效应”，更好地保持图像的边缘、纹理细节信息。
It is important to preserve edges and textures in SAR image denoising. First of all, modeling image by fractional-order derivative and negative Sobolev space, this paper presents a fractional-order multi-scale variation PDE model, and the proposes the adaptive parameter selection method and obtains the field and scale adaptively algorithm for SAR image denoising. Numerical experiments show that the new method can restrain the “blocky effect” and preserve more edges and textures in the processing of noise removal.
韦志辉、张军
雷达遥感技术计算技术、计算机技术
相干斑噪声抑制分数阶导数多尺度变分法自适应参数
speckle noise removalfractional-order derivativemulti-scalevariation methodadaptive parameter
韦志辉,张军.SAR图像去噪的分数阶多尺度变分PDE模型及自适应算法[EB/OL].(2009-12-31)[2025-08-02].http://www.paper.edu.cn/releasepaper/content/200912-1225.点此复制
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