COMPARATIVE ANALYSIS OF META HEURISTIC NATURE-INSPIRED TECHNIQUES FOR IMAGE CONTRAST ENHANCEMENT

Image contrast enhancement plays a pivotal role in improving perceptual quality.The images with limited contrast are often susceptible to noise and suffer from reduced visual appearance, making them difficult to analyze and process effectively.Highquality images play a major role in several applications where precise interpretation is required for accurate analysis ,diagnosis and decision making.The existing methods of Histogram Equalization, Contrast Stretching aim to provide the improved contrast but require the manual tuning of parameters.Nature inspired algorithms brings out the necessity of automatic tuning and complex problem-solving situations.The emphasis of this paper is a Modified Histogram Extended-PSO(MHE-PSO) algorithm proposed to enhance the low contrast images.Primarily three major nature inspired methods such as Genetic Algorithm (GA), Firefly Algorithm (FA), Particle Swarm Optimization (PSO) are implemented.The performances are compared in terms of Mean Square