基于小波阈值优化和边缘检测的SAR影像斑点噪声滤除

SAR Image De-noise Based Wavelet Threshold-optimization and Edge-detection Using Wavelet

探讨在小波频域内进行SAR斑点噪声分析的特点和优势 ,回顾小波频域斑点噪声滤除的方法 ,结合前人阈值优化和边缘检测的思想提出一种新的斑点噪声滤除方法。试验表明所研究的噪声滤除方法 ,同各种空间域滤波方法和已有的小波频域滤波方法比较 ,在噪声滤除和信息保留两方面的综合效果有明显提高 ,具有一定的应用价值。

Speckle is an important characteristic of SAR image that obstructs the efficient interpretation and thus its applications. So,the image filtering is indispensable in the SAR related applications.In the SAR filtering,there is a persistent contradiction:constraining noises VS.keeping image details.In other words,the optimal goal of image filtering is to constrain the noises while keeping the image details at the same time. The traditional filters are mostly those in the space domains.Though developments of filters in space domain have gradually shortened the span of the two sides,there still are some difficulties in overcoming such contradiction.So,the filters in frequency domain have attracted more and more attention. In wavelet frequency domain,the image frequency can be efficiently decomposed and then the noise can be restricted.In the paper,the de-noise filters in frequency are analyzed and compared.Then based on the concepts of threshold-optimizing and edge-detecting in wavelet frequency domain,an new wavelet de-noise method is presented.The experiment shows that the new filter is efficient at both noise constraining and image detail keeping.