小波模拟退火-软阈值SAR图像降噪算法

提出了一种新的SAR(Synthetic Aperture Radar)图像降噪方法,利用小波变换对空间位置信息保留的特性,依据小波变换后近似图像仍满足吉布斯分布,将模拟退火算法引入到小波域中,首先,根据SAR功率图像斑点的特性,对传统的同态变换方法做出了相应的修正,大大降低了处理结果的辐射偏差,提高了等效视数,然后在多分辨率理论和小波变换理论基础上,选用适合特定图像的最优小波基进行分解,最后对小波变换后的近似图像进行模拟退火处理,对各个细节图像有选择地进行软阈值处理.实验证明,此方法比传统的小波降斑取得了更好的平滑效果,比传统模拟退火大大减少了处理的时间,同时对图像的辐射精度的保持,斑点的抑制,以及边缘保持都有较满意的结果. 

Combined simulated annealing and soft-threshold wavelet de-noising of SAR image

A technique of speckle reduction in synthetic aperture radar(SAR) images was presented.Based on the character of wavelet transforms that the approximate coefficients of the transformed image still obey Gibbs distribution,the simulated annealing to the wavelet domain was introduced.The traditional logarithmic transformation was modified to adapt the power SAR images,which can maintain the mean of the SAR image better and achieve a better equivalentlook,then based on multi-resolution analysis theory and wavelet transform theory,an optimal mother wavelet was found to match the specific images.The algorithm of simulated annealing was applied to the coefficient in the scaling subspace and the algorithm of soft-thresholding was applied to the coefficient in the wavelet subspace distinctively.The result of experiments show that the new technique achieves a better smooth result when compared to the traditional wavelet denoising,at the same time it saves much time when compared to the simulated annealing,and it improves the structure and edge preservation with satisfying denoising results.