Noise removal using smoothed normals and surface fitting

被引：175

作者：

Lysaker, M

Osher, S

Tai, XC

机构：

[1] Henan Univ, Math Inst, Kaifeng 475001, Peoples R China

[2] Univ Bergen, Dept Math, N-5008 Bergen, Norway

[3] Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90024 USA

来源：

IEEE TRANSACTIONS ON IMAGE PROCESSING | 2004年 / 13卷 / 10期

基金：

美国国家科学基金会;

关键词：

anisotropic diffusion; image denoising; nonlinear partial differential equations (PDEs); normal processing;

D O I：

10.1109/TIP.2004.834662

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, we use partial differential equation techniques to remove noise from digital images. The removal is done in two steps. We first use a total-variation filter to smooth the normal vectors of the level curves of a noise image. After this, we try to find a surface to fit the smoothed normal vectors. For each of these two stages, the problem is reduced to a nonlinear partial differential equation. Finite difference schemes are used to solve these equations. A broad range of numerical examples are given in the paper.

引用

页码：1345 / 1357

页数：13

共 28 条

[1]

Ballaster C., 2000, IEEE T IMAGE PROCESS, V9, P1200

[2]

BERTOZZI AL, 2003, 0326 U CAL

[3] SEGMENTATION THROUGH VARIABLE-ORDER SURFACE FITTING [J].