TY - GEN
T1 - Geometry-driven nonlinear equation with an accelerating coupled scheme for image enhancement
AU - Fu, Shujun
AU - Ruan, Qiuqi
AU - Mu, Chengpo
AU - Wang, Wenqia
PY - 2007
Y1 - 2007
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/37249084793
U2 - 10.1007/978-3-540-72584-8_65
DO - 10.1007/978-3-540-72584-8_65
M3 - Conference contribution
AN - SCOPUS:37249084793
SN - 9783540725831
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 490
EP - 496
BT - Computational Science - ICCS 2007 - 7th International Conference, Proceedings, Part I
PB - Springer Verlag
T2 - 7th International Conference on Computational Science, ICCS 2007
Y2 - 27 May 2007 through 30 May 2007
ER -