Open AccessAn adaptive total variational despeckling model based on gray level indicator frame
Author(s) -
Yu Zhang,
Songsong Li,
Zhichang Guo,
Boying Wu
Publication year - 2021
Publication title -
inverse problems and imaging
Language(s) - English
Resource type - Journals
eISSN - 1930-8345
pISSN - 1930-8337
DOI - 10.3934/ipi.2020068
Subject(s) - uniqueness , regularization (linguistics) , multiplicative function , multiplicative noise , mathematics , noise reduction , computer science , total variation denoising , minification , regular polygon , algorithm , mathematical optimization , artificial intelligence , mathematical analysis , geometry , signal transfer function , digital signal processing , analog signal , computer hardware
For the characteristics of the degraded images with multiplicative noise, the gray level indicators for constructing adaptive total variation are proposed. Based on the new regularization term, we propose the new convex adaptive variational model. Then, considering the existence, uniqueness and comparison principle of the minimizer of the functional. The finite difference method with rescaling technique and the primal-dual method with adaptive step size are used to solve the minimization problem. The paper ends with a report on numerical tests for the denoising of images subject to multiplicative noise, the comparison with other methods is provided as well.