Geometry-driven nonlinear equation with an accelerating coupled scheme for image enhancement

Shujun Fu*, Qiuqi Ruan, Chengpo Mu, Wenqia Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this paper, a geometry-driven nonlinear shock-diffusion equation is presented for image denoising and edge sharpening. An image is divided into three-type different regions according to image features: edges, textures and details, and flat areas. For edges, a shock-type backward diffusion is performed in the gradient direction to the isophote line (edge), incorporating a forward diffusion in the isophote line direction; while for textures and details, a soft backward diffusion is done to enhance image features preserving a natural transition. Moreover, an isotropic diffusion is used to smooth flat areas simultaneously. Finally, a shock capturing scheme with a special limiter function is developed to speed the process with numerical stability. Experiments on real images show that this method produces better visual results of the enhanced images than some related equations.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I
PublisherSpringer Verlag
Pages490-496
Number of pages7
ISBN (Print)9783540725831
DOIs
Publication statusPublished - 2007
Event7th International Conference on Computational Science, ICCS 2007 - Beijing, China
Duration: 27 May 200730 May 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4487 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Conference on Computational Science, ICCS 2007
Country/TerritoryChina
CityBeijing
Period27/05/0730/05/07

Fingerprint

Dive into the research topics of 'Geometry-driven nonlinear equation with an accelerating coupled scheme for image enhancement'. Together they form a unique fingerprint.

Cite this