Global total variation minimization

被引：39
|
作者：
Dibos, F
Koepfler, G
机构：
[1] Univ Paris 09, CNRS, URA 749, CEREMADE, F-75775 Paris 16, France
[2] Univ Paris 05, UFR Math & Informat, PRISME, F-75270 Paris, France
来源：
SIAM JOURNAL ON NUMERICAL ANALYSIS | 2000年 / 37卷 / 02期
关键词：
total variation; image denoising; minimization; level set;
D O I：
10.1137/S0036142998334838
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The minimization of the total variation is an important tool of image processing. A lot of authors have addressed the problem and developed algorithms for image denoising. In this paper we present an alternative approach of the total variation minimization problem. After an introduction to the topic and a review of related work, we give a short development of the bounded variation (BV) background. Then we present our global total variation minimization model and proof its validity. Furthermore we introduce a practical algorithm which handles digital image data and we give experimental results.
引用
收藏
页码：646 / 664
页数：19
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