A New Efficient Approach for Removal of High Density Salt and Pepper Noise in Videos Using Modified Decision Based Unsymmetric Trimmed Median Filter

A new and efficient algorithm for high-density salt and pepper noise removal in videos is proposed. The proposed algorithm uses a modified decision based unsymmetric trimmed median filter to remove the high density salt and pepper noise. This filter restores the gray scale, and color images that are highly corrupted by salt and pepper noise. The existing methods are Standard median filter (MF), Decision based algorithm (DBA), Modified decision based algorithm (MDBA), and Progressive switched median filter (PSMF). The proposed method can removes the high density noise, its computational speed is also higher than existing filters, it will take the feedback from noisy or corrupted pixels. The proposed algorithm is tested against Different gray scale and color images and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF). Results of the algorithm is compared with various existing algorithms and it is proved that the new method has better visual appearance and quantitative measures at higher noise densities as high as 90%.