Image vector quantization coding based on genetic algorithm
Ying Liu, Hui Min Zhou, Yu Wen-fang · 2004
Genetic algorithms (GAs) are a part of evolutionary computing, which is a rapidly growing area of artificial intelligence. They exploit the ideas of the survival of the fittest and an interbreeding population to create a novel and innovative search strategy. Vector quantization (VQ) has been commonly used in the compression of image and speech signals. In this paper a new approach to image compression using vector quantization technique is presented. Genetic algorithm (GA) is used to design image VQ codebook, and it is found that GA is a more robust search in the global optimum and is computationally simpler than other algorithms such as LBG algorithm. The whole process of using GA for image VQ codebook design is discussed in detail and its performance is evaluated through some experiment results.