A Decision Based Unsymmetrical Trimmed Modified Winsorized Mean Filter for the Removal of High Density Salt and Pepper Noise in Images and Videos

A Novel Decision based Unsymmetrical Trimmed modified winsorized mean algorithm, which uses modified winsorized mean rather than conventional median for the restoration of gray scale and color images that are heavily corrupted by salt and pepper noise is proposed. The processed pixel is checked for 0 or 255; if examined pixel is equal to 0 or 255, then it is considered as noisy pixel else not noisy. The noisy pixel is replaced by modified winsorized mean of the unsymmetrical trimmed array. The non noisy pixel is left unaltered. The proposed algorithm eliminates the salt and pepper noise by preserving fine details of an image even at high noise densities. The proposed algorithm shows excellent results quantitatively and qualitatively when compared to existing and recently filters. The proposed algorithm is tested against different images of varying details, which gives higher Peak Signal-to-Noise Ratio (PSNR), Image Enhancement Factor (IEF), Structural Similarity Index Metric (SSIM) and low Mean square error(MSE). The information preserving capability is evaluated using Pratt's FOM, which yielded very good result even at high noise densities. The visual quality of the proposed algorithm after noise removal was found good at high noise densities.