基于多小波域Besov球映射的SAR图像去噪算法

SAR image denoising using multiple wavelet domains Besov balls projections

针对单小波域难以准确描述SAR图像不同平滑区域特征的不足,提出一种基于多小波域Besov球映射去噪算法。首先利用统一小波隐马尔可夫树模型和Besov标准求一组小波基Besov球半径,然后交替使用基于不同小波基的Besov球映射算法估计原始图像信息。实验结果表明,该算法具有很好的去噪效果和边缘结构保护能力,大大优于其他单一小波去噪算法。

Different smoothing regions of SAR image can not be represented accurately in single wavelet domain. In order to solve this problem, a Besov ball projections algorithm in multiple wavelet domains was proposed. Different Besov balls＇ radius were defined by the universal hidden Markov tree model and Besov norm, then an image was projected onto alternate Besov balls of proper radius corresponding to the projection onto convex sets algorithm based on preserving edge and strong scatterers （SPOCS） for image denoising. Experimental results demonstrate that this method can not only provide significant improvement over conventional algorithms based on single wavelet domain, but also preserve edge structure better.