Image Contrast Enhancement using Fuzzy Technique with Parameter Determination using Metaheuristics
This work addresses image quality enhancement for visual applications, but it is incremental as it combines existing techniques like fuzzy systems and metaheuristics.
The authors tackled image contrast enhancement by developing an image-specific transformation using a fuzzy system tuned with genetic algorithm and hill climbing, selecting two superior variants based on fitness and a survey indicating one method visually improves contrast.
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.