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Applications Research of Improved Genetic Algorithm in Image Denoising

机译:改进遗传算法在图像去噪中的应用研究

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In the process of generation, transmission and recording, image signals are often disturbed by various noises, which seriously affect the visual effect of images. Noise is the main factor affecting image quality, which has a great influence on the subsequent processing of images. Therefore, it is of great practical significance to adopt appropriate methods to reduce noise. In this paper, several common methods of image noise removal are introduced, and the denoising quality evaluation model is given. The traditional genetic algorithm has the characteristics of slow convergence and big relevant error in image denoising. We improved the genetic algorithm and applied it into image denoising. Experimental results show that the improved genetic algorithm has faster convergence speed and smaller relative error, which improves the efficiency and quality of image denoising.
机译:在生成,传输和记录的过程中,图像信号通常被各种噪声所干扰,这严重影响图像的视觉效果。噪声是影响图像质量的主要因素,这对随后的图像处理具有很大的影响。因此,采用适当方法降低噪音是具有巨大的现实意义。在本文中,引入了几种常见的图像噪声去除方法,并给出了去噪质量评估模型。传统的遗传算法具有缓慢收敛性和图像去噪中的大相关误差的特征。我们改进了遗传算法并将其应用于图像去噪。实验结果表明,改进的遗传算法具有更快的收敛速度和更小的相对误差,从而提高了图像去噪的效率和质量。

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