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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01-07

AUTHORS

Zhuang Fang, Xuming Yi

ABSTRACT

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. More... »

PAGES

1-22

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11042-018-7137-4

DOI

http://dx.doi.org/10.1007/s11042-018-7137-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111247882


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