A new algorithm for image denoising based on tetrolet transform

摘要

This paper introduces a new class of denoising function that has continuous derivative for image denoising. And a new algorithm are presented. First, we apply tetrolet transform to noise image and obtained tetrolet coefficient. Second, by using the new denoising function, we present an adaptive method based on SURE Risk. Instead of the global hard-thresholding algorithm for image denoising, we minimize an estimate of the mean square error by using adaptive genetic algorithm. At last Numerical experiments show that the proposed new algorithm can significantly outperform the original hard-thresholding method both in terms of PSNR and in visual quality.