基于自适应窗和形状自适应小波变换的SAR图像相干斑抑制

SAR IMAGE DESPECKLING BASED ON ADAPTIVE WINDOW AND SHAPE ADAPTIVE-DISCRETE WAVELET TRANSFORM

结合SAR图像空域的先验知识和小波域系数的特性,提出了一种新的SAR图像相干斑抑制算法.使用最近提出的局部多项式近似-置信区间交叉(local polynomial approximation-intersection of confidence intervals(LPA-ICI))构造自适应窗,寻找到与SAR图像中每个像素点相对应的同质区域,在每个同质区域内利用本文给出的快速形状自适应小波变换进行硬阈值收缩抑斑,最后根据本文提出的稀疏加权方法融合多个估计样本获得最终抑斑图像.实验结果表明本文提出的算法有着很好的抑斑性能,尤其是在去除重构图像中的"振铃"效应以及有效保留原始SAR图像中的点目标方面性能更突出.

By considering the prior knowledge of SAR image in spatial domain and the property of coefficients in wavelet domain, a novel algorithm of SAR image despeckling was presented. An adaptive window was constructed and a uniform region for every pixel of SAR image was found by using local polynomial approximation-intersection of confi- dence intervals （LPA-ICI）. Hard-threshold shrinkage despeckling was implemented with fast shape adaptive discrete wavelet transform proposed in this paper. At last, many despeckled samples were fused into a final despeckled SAR image according to the sparsity of regions. Experiments show that the algorithm proposed here has advanced despeeking performance. Especially, reconstructed image has no unpleasant ringing artifacts, and it efficiently reserves point targets of original SAR image.