基于四点插值细分小波的SAR图像去噪

针对SAR图像去噪过程中存在降低相干斑与保持有效细节这一矛盾,提出了一种基于四点插值细分小波的SAR图像去噪算法,该方法将小波和细分方法相融合,将四点插值细分规则应用到细分小波中,提出了图像去噪的新方法.该算法先用四点插值细分小波对原始图像进行分解,然后用Bayes自适应阈值及阈值函数对图像进行去噪,最后对去噪的小波系数进行重构,并通过等效视数、边缘保持指数等评价指标对去噪结果进行了评价.实验结果表明,算法的等效视数、边缘保持指数都有所提高,去噪效果得到了优化.

Image Denoising based on Four-point Interpolation Subdivision Wavelet

In order to solve the contradiction of reducing speckle and effective keeping details in speckle filtering for SAR(Synthetic Aperture Radar)images,an new image denoising method is presented,which is based on four-point interpolation subdivision wavelet.The method combines the wavelet with subdivision,and applies the rules of four-point interpolation subdivision to subdivision wavelet.In this paper,firstly the four-point interpolation subdivision wavelet is used to decompose the given SAR image.Then we reduce the noise of the wavelet coefficients by using adaptive threshold of Bayes estimation and the smooth threshold function.Finally,a technique is developed to reconstruct the denoising wavelet coefficients.The experimental results are evaluated by two evaluation indexes including equivalent number of looks(ENL)and edge save index(ESI).It shows that the method proposed in this paper is a more effective.