边缘检测的混合量子遗传算法

HYBRID GENETIC QUANTUM ALGORITHM TO EDGE DETECTION

本文基于费用函数最小化方法,提出一种混合量子遗传算法用于图像的边缘检测。量子遗传算法是一种基于量子计算的概念和理论的进化算法,它采用量子编码来表征染色体,能够表示出解的线性叠加态,比传统的遗传算法具有更好的群体多样性和全局寻优能力。我们将这一算法和局部搜索算法相结合,用于图像的边缘检测问题,产生了令人满意的检测效果,并对噪声有较好的抑制作用。

In this paper we present a hybrid genetic quantum algorithm (HGQA) based on cost minimization technique for edge detection. GQA is based on the concept and principles of quantum computing, which can represent a linear superposition of solutions. Thus, GQA has a better characteristic of diversity and better global search capability than classical approaches. We combine GQA and the local search technique to the problem of edge detection. Experiment results show the algorithm perform very well in terms of quality of the final edge image, rate of convergence and robustness to noise.