Abstract
AbstractIn an image processing system, image enhancement plays a crucial role. Improvement of image quality by maximizing the information in the given input image is the main aim of this paper. Adaptive histogram equalization and histogram equalization are most popular non-heuristic or classical techniques for image enhancement by preserving main features of the input image. These techniques failed in achieving good quality enhancement. Optimization techniques have been proposed for enhancement of image problem. The quality is enhanced by selecting the optimal parameters based on objective function formulated during optimization process. The formulation of objective function plays an important role in optimization problem. This paper offers an effective objective approach for image enhancement using constriction factor-based particle swarm optimization (CPSO) algorithm. The proposed algorithm has been tested on medical images like knee cyst, spine MRI, and liver tumor. The proposed algorithm is successful in improving the quality of these images.KeywordsImage enhancementConstriction factor-based PSO algorithmImage quality enhancementPSNRRMSE
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