Adaptive wavelet threshold for image denoising

Threshold selection is the critical issue in image denoising via wavelet shrinkage. Many powerful approaches have been investigated, but few have been to make the threshold values adaptive to the changing statistics of images and meanwhile maintain the efficiency of the algorithm. In this work an efficient adaptive algorithm to capture the dependency of inter-scale wavelet coefficients is proposed. Experiments show that higher peak signal-to-noise ratio can be obtained as compared to other threshold-denoising algorithms.