Image Quality Assessment based on Fuzzy Logic

• Baljinder
• Anuj Mehta

Image Quality Assessment, HVS Model, Image Noise, Fuzzy

This paper presents algorithm for image quality assessment based on fuzzy logic. First, a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input evaluates detail losses and additive impairments for image quality assessment. The detail loss refers to the loss of useful visual information which affects the content visibility, and the additive impairment represents the redundant visual information whose appearance in the test image will distract viewer’s attention from the useful contents causing unpleasant viewing experience.. Noise is usually quantified by the percentage of pixels which are corrupted. Corrupted pixels are either set to the maximum value or have single bits flipped over. So the main objective of this dissertation work is to get almost an actual image from the corrupted image and then finding the fine edges in the image using fuzzy logic.

Published

 Vol. 2 Issue. 3 Pages. 3135-3139

Baljinder, Anuj Mehta. "Image Quality Assessment based on Fuzzy Logic".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 3, pp.3135-3139, URL :https://rjwave.org/ijedr/papers/IJEDR1403053.pdf

Volume 2 Issue 3 

Pages. 3135-3139

Published Paper PDF : https://rjwave.org/ijedr/papers/IJEDR1403053.pdf

Published Paper URL : https://openrgate.org/viewfulldetails.php?id=885

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition