A New Initialization Method and a New Update Operator for Quantum Evolutionary Algorithms in Solving Fractal Image Compression

Abstract

Fractal Image Compression (FIC) problem is a combinatorial problem which has recently become one of the most promising encoding technologies in the generation of image compression. While Quantum Evolutionary Algorithm (QEA) is a novel optimization algorithm proposed for class of combinatorial optimization problems, it is not widely used in Fractal Image Compression problem yet. Using statistical information of range and domain blocks, and a novel magnetic update operator, this paper proposes a new algorithm in solving FIC. The statistical information of domain and range blocks is used in the initialization step of QEA. In the proposed update operator the q-individuals are some magnetic particles applying attractive force to each other. The force two particles apply to each other depends on their fitness and their distance. The proposed algorithm is tested on several images and the experimental results show better performance for the proposed algorithm than QEA and GA. In comparison with the full search algorithm, the proposed algorithm reaches comparable results with much less computational complexity.