A genetic algorithm for solving a new image restoration model based on selective filtering

Nour-eddine Joudar, Fidae Harchli, Es-Safi Abdelatif, M. Ettaouil
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Abstract

Image restoration problem is a very interesting field which preserves its importance until now. This field has some drawbacks, from one hand, it suffers from the high complexity to solve the classical model, on other hand, it causes a deterioration of some parts in the original image that we want to restore. In this context, we propose in this paper a modified model for image restoration based on the addition of a decision variable. This later controls the restoration in each pixel which is a helpful step to preserve areas that had a good quality. To solve the new model we propose the genetic algorithm which is more robust and suitable for this kind of optimization problem.
基于选择性滤波的遗传算法求解一种新的图像恢复模型
图像恢复问题是一个非常有趣的领域,至今仍保持着它的重要性。该领域存在一定的弊端,一方面是求解经典模型的复杂度较高,另一方面是会导致我们想要还原的原始图像中某些部分的退化。在此背景下,本文提出了一种基于决策变量的改进图像恢复模型。稍后控制每个像素的恢复,这是一个有用的步骤,以保留具有良好质量的区域。为了求解新模型,我们提出了一种鲁棒性更强的遗传算法,适合于求解这类优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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