Locally adaptive image denoising based on bivariate shrinkage function
基于双变量收缩函数的局域自适应图像去噪

JP3]To improve the performance of image-denoising methods, a locally adaptive denoising algorithm was presented. The new algorithm assumed the statistical dependence among wavelet coefficients. First, a bivariate probability distribution model was introduced to model the statistics of wavelet coefficients, and corresponding nonlinear threshold function (bivariate shrinkage function) was derived from the model using the Bayesian estimation theory. Secondly, using locally variance estimation, a locally adaptive image-denoising algorithm was presented. Also this algorithm could be applied to the complex wavelet domain. Experimental results and comparision analysis are given to illustrate the effectiveness of this denoising algorithm.