An efficient detection technique for removing random-valued impulse noise in images

摘要

In this paper we propose a new technique to detect random-valued impulse noise in images. In this method, the noisy pixels are detected iteratively through several phases. In each phase, a pixel will be marked as a noisy pixel if it does not have sufficient number of similar pixels inside the neighborhood window. The size of the window increases over the phases, so does the sufficient similar neighbor criterion. After the detection phases, all noisy pixels will be corrected in a recovering process. We compare the performance of this method with other recently published methods, in terms of peak signal to noise ratio and perceptual quality of the restored images. From the simulation results we observe that this method outperforms all other methods at medium to high noise rates. The algorithm is very fast, providing consistent performance over a wide range of noise rates. It also preserves fine details of the image.