IMAGE NOISE REMOVAL BASED ON TOTAL VARIATION

被引：16

作者：

Thanh, D. N. H. ^{[1
]}

Dvoenko, S. D. ^{[1
]}

机构：

[1] Tula State Univ, Tula, Russia

来源：

COMPUTER OPTICS | 2015年 / 39卷 / 04期

关键词：

total variation; ROF model; Gaussian noise; Poisson noise; image processing; biomedical image; Euler-Lagrange equation;

D O I：

10.18287/0134-2452-2015-39-4-564-571

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Today, raster images are created by different modern devices, such as digital cameras, X-Ray scanners, and so on. Image noise deteriorates the image quality, thus adversely affecting the result of processing. Biomedical images are an example of digital images. The noise in such raster images is assumed to be a mixture of Gaussian noise and Poisson noise. In this paper, we propose a method to remove these noises based on the total variation of the image brightness function. The proposed model is a combination of two famous denoising models, namely, the ROF model and a modified ROF model.

引用

页码：564 / 571

页数：8

共 29 条

[11] A variational approach to reconstructing images corrupted by poisson noise [J].