A novel natural image noise level estimation based on flat patches and local statistics

被引:20
作者
Fang, Zhuang [1 ,2 ]
Yi, Xuming [1 ]
机构
[1] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Hubei, Peoples R China
[2] Hubei Univ Nationalities, Sch Sci, Enshi 445000, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Noise level estimation; Flat patches; Gaussian noise; Eigenvalue; Covariance matrix; ALGORITHM;
D O I
10.1007/s11042-018-7137-4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a high-precision algorithm for noise level estimation. Different from existing algorithms, we present a new noise level estimation algorithm by linearly combining the overestimated and underestimated results using combinatorial coefficients that can be tailored to the problem at hand. The algorithm has two distinct features: it avoids the underestimation of noise level estimation algorithms that employ the minimum eigenvalue and demonstrates higher accuracy and robustness for a large range of visual content and noise conditions. The experimental results that are obtained in this study demonstrate that the proposed algorithm is effective for various scenes with various noise levels. The software release of the proposed algorithm is available online at https://ww2.mathworks.cn/matlabcentral/fileexchange/64519-natural-image-noise-level-estimation-based-on-flat-patches-and-local-statistics.
引用
收藏
页码:17337 / 17358
页数:22
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