A Review on Fractal Image Compression Using Optimization Techniques

Abstract

Image compression is an important process that has many possible application areas. The major blemish of fractal image compression is the time consuming compared to other image compression approaches. Image compression is the most essential requirement for efficient utilization of storage space and transmission bandwidth. Image compression techniques are responsible for decreasing the size of the image and keeping the quality of the recovered image. Presently many image compression algorithms are utilized to deal with the growing number of data concerned; still, area of research is to find an alternative solution to this problem. Therefore, to overcome this obstacle uses optimization techniques to solve this problem and reduces search space to find self-similarity in the given image. This review provides a study of many these techniques like Genetic Algorithm (GA), Crowding Optimization Method (COM), Particle Swarm Optimization (PSO) and Harmony Search Algorithm (HAS) and how using them in fractal image compression.