DocumentCode
2985681
Title
Nonlocal means algorithm using superformula kernel for image denoising
Author
Lunbo Chen ; Yicong Zhou ; Chen, C.L.P.
Author_Institution
Dept. of Comput. & Inf. Sci., Univ. of Macau, Macau, China
fYear
2013
fDate
22-25 Oct. 2013
Firstpage
1
Lastpage
4
Abstract
Using the superformula, a mathematic function describing many complex shapes and curves, this paper designs a new superformula kernel (SFK). We then introduce a novel nonlocal means (NLM) algorithm for image denoising by replacing the Gaussian kernel with the SFK. Simulations and comparisons demonstrate that the proposed kernel and algorithm show excellent denoising performance in terms of the peak signal and ratio (PSNR) and structural similarity (SSIM).
Keywords
AWGN; Gaussian distribution; image denoising; Gaussian kernel; NLM algorithm; PSNR; SFK; SSIM; image denoising; mathematic function; nonlocal means algorithm; peak signal-to-noise ratio; superformula kernel; Image denoising; Kernel; Noise level; Noise measurement; Noise reduction; PSNR; Image denoising; Nonlocal Means; Superformula kernel; peak signal and ratio; structural similarity;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON 2013 - 2013 IEEE Region 10 Conference (31194)
Conference_Location
Xi´an
ISSN
2159-3442
Print_ISBN
978-1-4799-2825-5
Type
conf
DOI
10.1109/TENCON.2013.6718973
Filename
6718973
Link To Document