This study proposes a new fuzzy adaptive filter for the restoration of impulse corrupted digital images. The proposed filter incorporates fuzzy functions to model the uncertainties, while detecting and correcting impulses. The traditional, SMALL fuzzy function is used to identify the non-impulsive nature of the detected corrupted pixels in the initial step. For the better restoration of detected impulsive pixels, a modified version of Gaussian function is utilised to determine the similarity among the detected uncorrupted pixels. The proposed correction scheme provides more weight to the uncorrupted pixels that show much similarity with other uncorrupted pixels in the window while replacing impulses. The proposed filter adapts to various noisy and image conditions and is capable of suppressing noise while preserving image details. The experimental results in terms of subjective and objective metrics favour the proposed algorithm than many other prominent filters in literature.
An effective median filter for salt & pepper impulse range signals. An additive noise process may corrupt these noise removal is presented. This computationally efficient filtering digital images in both the acquisition and transmission stages. technique is implemented by a two pass algorithm: In the first Application-specific image filtering algorithms are needed to pass, identification of corrupted pixels that are to be filtered are simultaneously remove the effects of the corruptive process perfectly detected into a flag image using a variable sized detection window approach; In the second pass, using the and preserve important features of the images. Impulse noise detected flag image, the pixels to be modified are identified and removal in image processing often involves the removal of corrected by a more suitable median. Experimental results show these salt and pepper noises from images which is a very that the proposed algorithm performs far more superior than important pre-processing step for most other subsequent many of the median filtering techniques reported in terms of processing tasks such as edge detection, segmentation and retaining the fidelity of the image highly corrupted by impulse classification. In this area, early advances were dominated by noises even to the tune of ninety percent impulse noise. The linear filtering. They have had enormous impact on the proposed algorithm is free from patchy effects, does not extend lmelterf They techad formous stationary black or white blocks in the image as has been found in many development of various techniques for processing stationary other adaptive median based techniques and is very effective in and non-stationary signals. However, there are a large number cases when images are corrupted with large percentage of impulse of situations where linear filtering approach performs poorly. noises. This algorithm works very well for images with lower The limitation is the inability to simultaneously eradicate noise percentage of impulse noises also.
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