基于广义交叉验证和Cycle Spinning的SAR图像相干斑抑制
doi: 10.3724/SP.J.1146.2006.01071
SAR Speckle Reduction Based on Generalized Cross Validation and Cycle Spinning
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摘要: 该文基于SAR图像的统计特性，提出了一种相干斑抑制算法。该算法在不需要估计噪声能量的情况下，采用广义交叉验证准则构造目标函数，自适应获取近似最优阈值；然后基于小波阈值收缩完成SAR图像滤波；并引入Cycle Spinning策略有效去除边缘存在的振铃效应。实验结果表明：基于该文算法的相干斑抑制在视觉效果和客观衡量指标上都取得了较好的、鲁棒的效果，有效地抑制了相干斑噪声，均匀区域平滑，且能同时保持边缘和细节清晰。Abstract: Considering the statistical characteristics of SAR images, a novel speckle reduction algorithm is presented in this paper. This technique is by virtue of generalized cross validation and constructs an object function to acquire the asymptotic optimal threshold without of estimating noise variance. After applying the wavelet shrinkage on SAR image, cycle spinning strategy is introduced to wipe off the visible ringing effects along the edges. Numerical tests show that the proposed SAR speckle reduction algorithm provides improvements both in visual effects and quantitative analysis, which can smooth image effectively and remain the edges and texture clearly.
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