Geometry-Driven Nonlinear Equation with an Accelerating Coupled Scheme for Image Enhancement

Authors:
Shujun Fu;Qiuqi Ruan;Chengpo Mu;Wenqia Wang
Affiliations:
School of Mathematics and System Sciences, Shandong University, Jinan, 250100, China and Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China;Institute of Information Science, Beijing Jiaotong University, Beijing, 100044, China;School of Aerospace Science and Technology, Beijing Institute of Technology, Beijing, 100081, China;School of Mathematics and System Sciences, Shandong University, Jinan, 250100, China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Year:
2007

Citing 8
Cited 0

Scale-Space and Edge Detection Using Anisotropic Diffusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-oriented image enhancement using shock filters

SIAM Journal on Numerical Analysis
Nonlinear Image Filtering with Edge and Corner Enhancement

IEEE Transactions on Pattern Analysis and Machine Intelligence
Signal and image restoration using shock filters and anisotropic diffusion

SIAM Journal on Numerical Analysis
Digital image processing

Digital image processing
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)

Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Image enhancement and denoising by complex diffusion processes

IEEE Transactions on Pattern Analysis and Machine Intelligence
Behavioral analysis of anisotropic diffusion in image processing

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

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.