HeNLM-LA: a locally adaptive non-local means algorithm based on hermite functions expansion

被引：0
|
作者：
N. V. Mamaev
A. S. Lukin
D. V. Yurin
机构：
[1] Moscow State University,The Faculty of Computational Mathematics and Cybernetics
来源：
Programming and Computer Software | 2014年 / 40卷
关键词：
Noise Level; Image Denoising; Hermite Function; Noise Reduction Algorithm; Noise Level Estimation;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A new noise reduction algorithm HeNLM-LA is proposed. It is a modification of the non-local means algorithm using Hermite functions expansion of pixel neighborhoods. The filtering strength parameter is automatically adjusted proportionally to the local noise level. An algorithm for local noise level estimation is based on edge modeling; it suppresses high-amplitude edges in the map of local image variance.
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页码：199 / 207
页数：8
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