Abstract
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Block artifact is one of the visually annoying problems that usually exist in low-bit-rate compression images and videos. In this paper, we propose a simple but effective method to reduce block artifact based on pixel classification in spatial domain and frequency domain corrupted with impulses, Gaussian noises, artifacts,(Blocking, Ringing, blur,etc..). In traditional methodology, linear filters are not effective in removal of multiplicative noises, impulses noises, and artifacts (Blocking, Ringing, blur,). And also it is large in amplitude; hence it dominates characterizations of the signals based on second-order statistics such as correlation and spectral analysis.This project aims to design a non linear adaptive based algorithm, smooth region and edge region (low pass filter is performed for image smoothening) by using a binary edge map from the edge detection process, for removing the artifacts (Blocking, Ringing, blurred,) also preserve edges and fine details in images and videos. This algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels and adaptive offset smoothing with the binary edge map is applied to reduce grid noise at block boundaries,( Edge detection: edge detection is performed using sobel edge detector.) Moreover extra edge-preserved filters used to remove block artifacts at edge region. And main advantage of the proposed algorithm is the uncorrupted pixels are unaltered and produced in the output. The appropriate filter is used based on the variance of the filter window, for estimating the value for replacing the corrupted value. This leads to reduced artifacts and high fine detail preservation at low bit rate compression image and videos. We have also added the simulation results we got in MAT lab, along with the program.
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