基于斑点方差估计的非下采样Contourlet域SAR图像去噪

 合成孔径雷达(SAR)图像固有的相干斑噪声严重影响图像质量,使得SAR图像的自动解译十分困难.本文联合SAR图像的统计特性和非下采样Contourlet对SAR图像细节信息的良好刻画能力,提出一种新的非下采样Contourlet域SAR图像去噪算法,通过估计到的各个高频方向子带的斑点噪声方差和变换系数模值的局部均值,对非下采样Contourlet变换系数进行判定,保留信号系数,抑制斑点噪声系数,实现SAR图像去噪.仿真实验结果表明,本文方法在斑点抑制的同时可以有效保持细节信息.

SAR Image Despeckling Based on the Estimation of Speckle Variance in Nonsubsampled Contourlet Domain

Synthetic aperture radar (SAR) images are inherently degraded by speckle noise, that severely affects the image qualities and makes the automatic interpretation of the image data very difficult. Combine the SAR image statistical property with the favorable capability of nonsubsampled contourlet transform on describing SAR images detail information, a novel SAR image despeckling method is presented. We estimate the speckle variance in each high-frequency directional subband. The local directional statistical information and the estimated speckle variance is used to classify the nonsubsampled contourlet transform coefficients as signal and noise coefficients. The SAR image despeckling is implemented by retaining signal coefficients and restraining noise coefficients. Experimental results demonstrate that the proposed despeckling method can preserve detail information effectively and reduce the speckle noise at the same time.