摘要
该文提出了一种比值距离像素相关性模型与相似像素选择的非局域SAR图像相干斑抑制算法。首先由两像素的联合概率密度函数得出了比值距离像素相关性模型,并按错误概率最小准则训练生成了不同情况下的像素相似性阈值表,然后进行非局域窗中像素的相似性计算,并用查表所得的像素相似性阈值进行非局域窗中相似像素的选择,最后用选中的像素进行当前像素真实后向散射系数的估计。对仿真与实测SAR图像的相干斑抑制实验显示,与其它现有非局域抑斑算法相比,该文方法不仅能最大程度地去除同质区域的噪声,而且可以对边缘纹理等细节区域进行很好地重构,滤波结果显示了很好的视觉效果,并且具有较低的计算复杂度。
Based on the ratio distance pixel-relativity and thresholding pixel-similarity, a modified non-local filter is proposed for SAR image despeckling in this paper. Firstly, the ratio distance pixel-relativity is obtained by transforming the joint probability density function of two pixels. Then, a table of pixel-similarity threshold, as a function of the SAR image look number and neighboring reflectivity ratio, is trained according to the minimum error probability. Finally, the pixel-similarity threshold is applied to select similar pixels from the searching window for the real reflectivity estimation. The proposed approach was verified by synthetic and real SAR images, and was compared with the PPB and LHRS-PRM filters. The visual quality and the quantification comparison show that the proposed approach is excellent not only in the reconstruction of the uniform area, the character of edges, texture, and details, but also with the lower computation eomolexitv.
基金
内蒙古自治区高等学校科学技术研究项目(NJZZ11069)
内蒙古自治区自然科学基金项目(2011BS0904)资助课题
