An adaptive total variational despeckling model based on gray level indicator frame

IF 1.5 4区数学 Q2 MATHEMATICS, APPLIED

Inverse Problems and Imaging Pub Date : 2020-01-01 DOI:10.3934/ipi.2020068

Yu Zhang, Songsong Li, Zhichang Guo, Boying Wu

引用次数: 4

Abstract

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.

查看原文本刊更多论文

基于灰度指标框架的自适应全变分去斑模型

针对带有乘性噪声的退化图像的特点，提出了构建自适应总变分的灰度指标。基于新的正则化项，提出了新的凸自适应变分模型。然后，考虑了泛函最小值的存在性、唯一性和比较原则。采用具有重标度技术的有限差分法和具有自适应步长的原对偶法来解决最小化问题。最后对乘性噪声下图像去噪的数值实验进行了报道，并与其他方法进行了比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Inverse Problems and Imaging 数学-物理：数学物理

CiteScore

2.50

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Inverse Problems and Imaging publishes research articles of the highest quality that employ innovative mathematical and modeling techniques to study inverse and imaging problems arising in engineering and other sciences. Every published paper has a strong mathematical orientation employing methods from such areas as control theory, discrete mathematics, differential geometry, harmonic analysis, functional analysis, integral geometry, mathematical physics, numerical analysis, optimization, partial differential equations, and stochastic and statistical methods. The field of applications includes medical and other imaging, nondestructive testing, geophysical prospection and remote sensing as well as image analysis and image processing. This journal is committed to recording important new results in its field and will maintain the highest standards of innovation and quality. To be published in this journal, a paper must be correct, novel, nontrivial and of interest to a substantial number of researchers and readers.