A Comparative Framework for Blocking Artifacts Removal of compressed Images using Fuzzy Logic

Abstract

Restoration of an image with blocking artifacts caused by low-bit-rate compression is a difficult task, and blocking artifact assessment techniques play an essential role in the computer vision area. An artifacts removal approach is a critical step in improving the image processing area's dependability and security, allowing for improved understanding in a variety of applications such as pattern recognition, object categorization, surveillance systems. Removal of artifacts is a processing technique that is utilized to give improved picture Quality, and several artifacts removal procedures have previously been used by researchers in the image processing era for this goal. However, when a collection of artifacts is present in an image such as line artifacts, motion artifacts etc. they do not yield acceptable outcomes. We have suggested a comparative methodology for removing line and motion artifacts from digital images utilizing fuzzy logic in this study. This study's key contribution is the creation of a novel fuzzy logic-based hybrid artifacts removal system that improves blocking artifacts efficiency. The suggested framework has its own influence on quality parameters to remove artifact from a picture.