Adaptive Techniques Based High Impulsive Noise Detection and Reduction of a Digital Image

As reducing impulse noise in a digital image is a very active research area in image processing, this paper proposes a novel algorithm for digital image impulsive noise detection and reduction based on adaptive nonlinear techniques which seems to be a boom in digital image restoration process. The main objective of this algorithm is to consider a particular digital image as input and make the preprocessing to remove the impulsive noise content by employing suitable adaptive nonlinear filter after identifying the impulsive noise of overall image. The proposed algorithm consists of two parts. First, identifying the type of noise present in the image as additive, multiplicative or impulsive by analysis of local histograms and secondly, denoising the detected impulsive noise by employing adaptive nonlinear filtering technique which comprises a process of adaptive noise identification of a corrupt pixel and filtering it by employing adaptive nonlinear filter. In this paper, a new adaptive noise identification and adaptive nonlinear filtering algorithm is described to detect and remove the impulsive noise. Noise present in the digital image should be removed in such a way that the important information of image should be preserved. A decision based nonlinear algorithm for elimination of impulsive noise in digital images has been described in this paper. In order to improve the performances of classical median filter, an adaptive nonlinear filter is proposed and results obtained have been compared. The proposed algorithm has been simulated on MATLAB GUI. A simulation result shows that the proposed algorithm effectively identifies and removes the high impulsive noise by preserving image originality compare to standard median filter.