A Novel Approach for Salt and Pepper Noise Removal using ROR and Contourlet Transform

Abstract

ROR and Contourlet transform is proposed to restore images corrupted by salt and pepper impulse noise. The operation is carried out in two stages, i.e., detection followed by filtering. For detection first, we propose the robust outlyingness ratio (ROR) for measuring how impulse like each pixel is, and then all the pixels are divided into four clusters according to the ROR values. Second, different decision rules are used to detect the impulse noise based on the absolute deviation to the median in each cluster. In order to make the detection results more accurate and more robust, the from-coarse-to-fine strategy and the iterative framework are used. In addition, the detection procedure consists of two stages, i.e., the coarse and fine detection stages. For filtering, proposed algorithm using contourlet transform (CT). Simulation results demonstrate that the proposed algorithm is better than traditional filters and is particularly effective for the cases where the images are very highly corrupted.