Open AccessA Skewness Fitting Model for Noise Level Estimation and the Applications in Image Denoising
Author(s) -
Bin Zhou,
Bi-Ying Zhong,
Jun Feng
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1871/1/012092
Subject(s) - skewness , noise (video) , noise reduction , variance (accounting) , parametric statistics , parametric model , image denoising , algorithm , estimation theory , statistics , computer science , mathematics , function (biology) , image (mathematics) , artificial intelligence , accounting , business , evolutionary biology , biology
In this paper, a novel noise level estimation technique is presented based on skewness fitting. The difference between exact skewness and observed value on each channel contributes to an objective function. The skewness concentration is helpful to guarantee the reasonability of the model. The optimal solution means an estimation of the noise variance and it is easy to be applied in some parametric denoising model. The accuracy and efficiency of proposed algorithm were verified by the numerical experiments.