DocumentCode
1778947
Title
Comparison of the PDE-Based Regularization Methods and a Unifying Framework
Author
Bochao Su ; Xiaohua Zhang ; Wanyu Liu ; Li Li
Author_Institution
HIT-INSA Sino French Res. Center for Biomed. Imaging, Harbin Inst. of Technol., Harbin, China
fYear
2014
fDate
18-20 Sept. 2014
Firstpage
527
Lastpage
532
Abstract
The frequent problems in computer vision consist of de-noising, artifact elimination as well as structure preserving or enhancing. PDE-based nonlinear diffusion filter may be one possibility to achieve those goals. In this paper, we perform comparison of three typical PDE-based regularization algorithms followed by the proposal of a general framework, which exploits fundamental significance for analyzing PDE-based regularization methods.
Keywords
computer vision; filtering theory; image denoising; PDE-based nonlinear diffusion filter; PDE-based regularization methods; artifact elimination; computer vision; denoising; Algorithm design and analysis; Coherence; Eigenvalues and eigenfunctions; Equations; Image edge detection; Noise reduction; Tensile stress; PDE; diffusion tensor; image processing; regularization;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 2014 Fourth International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-6574-8
Type
conf
DOI
10.1109/IMCCC.2014.114
Filename
6995084
Link To Document