Image Contrast Enhancement using Fuzzy Technique with Parameter Determination using Metaheuristics

TL;DR

This paper proposes an image contrast enhancement method using fuzzy systems optimized by metaheuristics like genetic algorithms and hill climbing, demonstrating improved visual quality through experimental evaluation.

Contribution

It introduces a novel image-specific contrast enhancement technique employing fuzzy systems tuned with metaheuristics, and evaluates its effectiveness through experiments and surveys.

Findings

Two variants outperform others in fitness evaluation

One variant significantly improves visual contrast

Method is effective across multiple images

Abstract

In this work, we have presented a way to increase the contrast of an image. Our target is to find a transformation that will be image specific. We have used a fuzzy system as our transformation function. To tune the system according to an image, we have used Genetic Algorithm and Hill Climbing in multiple ways to evolve the fuzzy system and conducted several experiments. Different variants of the method are tested on several images and two variants that are superior to others in terms of fitness are selected. We have also conducted a survey to assess the visual improvement of the enhancements made by the two variants. The survey indicates that one of the methods can enhance the contrast of the images visually.