关键词: 量子遗传算法, 二维最大熵, 图像分割

Abstract: With high computing complexity, traditional 2-D maximum entropy method is a defective method in image segmentation, although many algorithms have been proposed to bear on this problem. Considering GQAs (Genetic Quantum Algorithm) ability to retain the diversity of population and to converge rapidly, a 2-D maximum entropy method based on GQA was put forward. Compared with 2-D maximum entropy method based on classical genetic algorithm in experiments, this method was proved to perform better.

Key words: GQA(Genetic Quantum Algorithm), 2-D maximum entropy, image segmentation