Blur reduction by a Multiplicative Multiresolution Decomposition MMD

A. Serir, Assia Hamadene, F. Kerouh
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引用次数: 3

Abstract

In this paper, a new blur reduction method based on the new concept of Multiplicative Multiresolution Decomposition is presented. This method turns on specific corrections of coefficients in MMD domain. To appreciate the proposed approach performances, one could consider the classical method based on Shock filters and blind deblurring. The conventional methods for assessment like PSNR and MSE are invalid since there is no correlation with human perception. Therefore one could propose to use metrics which quantify the quantity of blur in images as it is proposed in [1]. In addition, one could compare the results visually and by plotting an original and deblurred transitions.
乘式多分辨率分解的模糊减少
基于乘法多分辨率分解的新概念,提出了一种新的模糊还原方法。该方法开启了MMD域系数的特定修正。为了评价该方法的性能,我们可以考虑基于冲击滤波器和盲去模糊的经典方法。由于PSNR和MSE与人的感知没有相关性,传统的评估方法是无效的。因此,可以像[1]中提出的那样,使用量化图像模糊量的指标。此外,人们还可以直观地比较结果,并绘制出原始的和去模糊的过渡。
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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