图像去模糊的单参数后处理方法

A. Krylov, A. Nasonov, Yakov Pchelintsev
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引用次数: 5

摘要

针对模糊图像的反卷积问题,存在着许多算法。但由于反卷积的病态性质,许多图像在去模糊后仍然模糊。为了进一步提高边缘区域模糊图像的质量,本文提出了一种边缘锐化算法。该方法基于像素网格扭曲,其主要思想是将像素向最近的图像边缘方向移动。翘曲可以使边缘更锋利,同时保持纹理区域几乎完整。针对不同的光学模糊模型进行了实验分析,优化了该方法的参数,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single parameter post-processing method for image deblurring
Numerous algorithms exist for the problem of deconvolution of blurred images. But due to ill-posed nature of deconvolution, many images still remain blurry after deblurring. An edge sharpening algorithm is proposed in the paper to further improve the quality of blurry images in edge areas. The method is based on pixel grid warping, its main idea is to move pixels in the direction of the nearest image edges. Warping allows to make edges sharper while keeping textured areas almost intact. Experimental analysis for different optical blur models is performed to optimize the parameters of the proposed method and to show its effectiveness.
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