Pixel Correlation-based Impulse Noise Reduction

Abstract

Median filtering based on switching is known that one of the most effective algorithms for reducing impulse noise. In this paper, we introduce a Pixel Correlation based Impulse Noise Reduction. The proposed algorithm consists of two main steps, detection and correction. In the first step, noise detection is performed using a scalable detection mask and morphological operation. In the second step, a corrupted pixel is corrected using the correlation between the uncorrupted pixels in the mask. The experimental results showed that the proposed method can reduce more impulse noise and preserve more edge information than state-of-the-art standard median filter and switching median filters (adaptive median filter and iterative adaptive switching median filter) by an average of 2.75 and 0.37 dB, respectively.