Fractal image compression by local search and honey bee mating optimization

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. in this paper a new technique is proposed that improves fractal image compression by use of no-search scheme and local search with honey bee mating optimization. This method improves the compression ratio, reduce the encoding time while retaining the quality of the retrieved image. Simulation results show that the proposed method gains superior performance over other fractal encoding algorithms.