High dimensional model representation median filter for removing salt and pepper noise

Abstract

In this paper, we introduce a novel method for noise reduction called the High-Dimensional Model Representation (HDMR) Median Filter. HDMR, functioning as a divide and conquer algorithm, dynamically adapts its filtering parameters based on local image characteristics. This adaptation aims to preserve image quality while efficiently eliminating noise. The HDMR Median Filter excels in retaining fine details, preserving edges, and safeguarding essential image features. To assess the performance of the proposed algorithm, we conducted comparisons with results from recent studies. These comparisons were based on two commonly used metrics: Structural Similarity (SSIM) and Peak Signal-to-Noise Ratio (PSNR) The obtained results demonstrate that the noise reduction algorithm obtained with HDMR performs better than the most recent studies in the literature.