A Nonlocal Image Denoising Algorithm Using the Structural Similarity Metric

被引：8
|
作者：
Dovganich, A. A. [1 ]
Krylov, A. S. [1 ]
机构：
[1] Moscow MV Lomonosov State Univ, Fac Computat Math & Cybernet, Moscow 119991, Russia
来源：
PROGRAMMING AND COMPUTER SOFTWARE | 2019年 / 45卷 / 04期
基金：
俄罗斯科学基金会;
关键词：
19;
D O I：
10.1134/S0361768819040029
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A new image denoising algorithm is proposed. It is a version of the nonlocal means (NLM) algorithm and uses a metric based on the CMCS modification of the structural similarity index (SSIM). The potentials of this metric for constructing the weighting function in the NLM method using the decomposition of this metric into components and specifying a physically justified weighting function for each component are demonstrated. The results produced by the modified method are compared with the results produced by the basic NLM algorithm, which uses the metrics L2 and SSIM for calculating the metric weights.
引用
收藏
页码：141 / 146
页数：6
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