REMOVAL OF HIGH DENSITY IMPULSE NOISE USING MORPHOLOGICAL BASED ADAPTIVE UNSYMMETRICAL TRIMMED MID-POINT FILTER

Abstract

A Morphological based Adaptive Unsymmetrical Trimmed Mid-Point Filter (MAUTMPF) for the restoration of gray scale images corrupted by salt and pepper noise for varying noise densities is proposed in this study. Images corrupted by impulsive noise severely hinder subsequent image processing tasks, such as edge detection, image segmentation, object recognition, etc. Therefore, it is absolutely essential to restore the original image from the corrupted image. The proposed algorithm replaces the corrupted pixel by mid point value out of the retained pixels other than 0’s and 255’s in a 3×3 window. The essential condition for the validity of the window is that at least two pixels in the selected window should be uncorrupted; if not the window size is incremented by 2. The iteration stops when the window size reaches 7. In particular case, when the condition for validity doesn’t hold in 7×7 window then the original 3×3 window is chosen and midpoint of minimum and maximum values of already processed pixels is replaced with the centre pixel. experimental evaluation using MATLAB reveals that our MAUTMPF shows better performance compared to the previous de-noising algorithms in terms of Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MSE) for noise densities up to 90%. The validity of the proposed algorithm is verified by testing it for different gray scale images.