DocumentCode
547340
Title
Monotonically decreasing eigenvalue for edge-sharpening diffusion
Author
Ma, Wenhua
Author_Institution
Sch. of Inf., Guangdong Univ. of Foreign Studies, Guangzhou, China
Volume
3
fYear
2011
fDate
10-12 June 2011
Firstpage
363
Lastpage
366
Abstract
Anisotropic diffusion is classified by the eigenvalue of the Hessian matrix associated with the diffusivity function into two categories: one incapable of edge-sharpening and the other capable of selective edge sharpening. A third class is proposed: the eigenvalue starts with a small value and decreases monotonically with image gradient magnitude so that the stronger the edge is, the more it is sharpened. Two such examples are given and one is found to consistently produce the best PSNR at all simulated noise levels.
Keywords
eigenvalues and eigenfunctions; image denoising; image enhancement; matrix algebra; Hessian matrix eigenvalue; anisotropic diffusion; diffusivity function; edge-sharpening diffusion; image denoising; image enhancement; image gradient magnitude; Anisotropic magnetoresistance; Eigenvalues and eigenfunctions; Image edge detection; Noise reduction; PSNR; Smoothing methods; Image enhancement; anisotropic diffusion; denoising; diffusivity; edge sharpening;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4244-8727-1
Type
conf
DOI
10.1109/CSAE.2011.5952698
Filename
5952698
Link To Document