Image Processing Technology Based on Multiple Population Genetic Algorithm

With the rapid development of information technology, image processing has been widely applied in numerous fields. This paper focuses on the application research of the multiple population genetic algorithm in image processing technology. As an efficient intelligent optimization algorithm, the multiple population genetic algorithm simulates the evolutionary process of biological populations, and it has stronger global search ability and faster convergence speed. In terms of image processing, this algorithm can effectively solve key problems such as image enhancement, restoration, reconstruction, segmentation, and matching. By elaborating the principle of the multiple population genetic algorithm in detail, deeply analyzing its specific applications in different image processing tasks, and combining a large number of experimental simulations, the performance of the algorithm is quantitatively evaluated using indicators such as information entropy and peak signal-to-noise ratio. Meanwhile, the experimental results are presented through visual charts. The research shows that the multiple population genetic algorithm has significant advantages in improving image quality, extracting image features, etc., providing new ideas and methods for the development of image processing technology in practical applications, and having important theoretical significance and practical application value.