A New and Efficient Method for Removal of High Density Salt and Pepper Noise Through Cascade Decision based Filtering Algorithm

Abstract

In this paper, a new and efficient cascade decision based filtering algorithm for the removal of high density Salt and Pepper Noise in images is proposed. The proposed algorithm is a cascaded filter employing a Modified Decision Based Median Filter as its first stage of operation. The second stage involves a combination of a new algorithm that calculates mean of difference in neighborhood pixels and a Modified Unsymmetric Trimmed Mean Filter. The proposed algorithm when compared with existing non-linear filters such as Standard Median Filter (SMF), Adaptive Median Filter (AMF), Decision Based Algorithm (DBA), Progressive Switch Median Filter (PSMF), Modified Decision Based Algorithm (MDBA) and Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) produces a better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF) even at high density salt and pepper noise. The proposed algorithm is tested for different images and the results are compared with other filters. The proposed algorithm results better in terms of image restoration and quantitative measures.