Abstract
Evolutionary computation is the cross-cutting and frontier research field of information science, automation science and computer science. It is also the research direction of computational intelligence. In this paper, based on the evolutionary computation theory, a series model of evolutionary computation is established and the convergence of typical evolutionary algorithms is analyzed. The adaptive evolutionary algorithm based on population information entropy and its application in image is proposed. The paper proposes a decision-making algorithm based on bit-coded discernible matrix and its application in image analysis. The idea of parallel computing is applied to the problem of SAR image change detection and image feature extraction. The corresponding parallel computing framework is designed to improve the running speed of the algorithm. Experimental results showed that the proposed algorithm can improve the accuracy and processing speed of the algorithm, which satisfies the practical application requirements.
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