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A Machine Learning Approach for Removal of JPEG Compression Artifacts: A Survey
2016
International Journal of Computer Applications
JPEG is a widely used image compression method. Though it is very efficient, it introduces certain artifacts and quantization noise. This paper is a detailed survey about various existing methods for the reduction of these artifacts. The paper explains each method and their advantages and drawbacks. Some of the methods mentioned are Weiner filtering, Image Optimization, Zero-masking, Local Edge regeneration, Multiple dictionary learning, Hybrid Filtering, Fuzzy filtering, Total Variation
doi:10.5120/ijca2016908732
fatcat:ag4oyo2cjvd4fd3syp55bpvczy