Cat Swarm Optimisation for Optimizing Hybridized Smoothening Filter in Image Edge Enhancement

Abstract

In this modern era, image transmission and processing plays a prominent role. It would not be possible to retrieve information from satellite and medical images without the help of Image processing techniques. Image edge enhancement is the art of examining images for identifying objects and judging their significance. The proposed work uses the concept of Cat swarm optimization Algorithm that proved to be the most powerful unbiased optimization technique for sampling a large solution space. Because of its unbiased stochastic sampling, it can quickly be adapted in image processing and thus for image edge enhancement as well. This paper deals with the techniques that help in improvising the quality of the image edges and in solving various complex image-processing tasks such as segmentation, feature-extraction, classification and image generation. The edge enhancement is done using hybridized smoothening filters by the cat swarm optimization algorithm and it has been compared to that of applying a genetic algorithm.

Keywords: Image edge enhancement, hybridized smoothening filter, Genetic algorithm (GA), Cat swarm optimization (CSO)

JEL Classification: C45