Image denoising using block classification in Contourlet domain

This paper presents a new image denoising method using block classification in Contourlet domain. The noise image is divided into 8×8 blocks. These blocks can be decomposed by the Contourlet into directional subbands while the block classification method provides the directional feature of input blocks. Based on this directional information, we propose the different thresholding processes with each input block. Thus, the new denoising algorithm proposed achieves better tradeoff between details retain and noises removal. Several experimental results show that the proposed new function is very effective and gives better performance both in terms of PSNR and in visual quality.