Title :
Efficient non-local kernel regression with structural classification for multiview image denoising
Author :
Zhou-Chi Lin;Jia-Fei Wu;Shing-Chow Chan
Author_Institution :
Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong
Abstract :
This paper presents an effective image structure classification method, which was recently proposed for selecting the key parameter of non-local kernel regression (NLKR) namely the kernel bandwidth. Meanwhile, to overcome the problem of intensive computation cost of the non-local patch searching in NLKR, a fast patch searching strategy is proposed according to the classified structure regions. The proposed structure-aware NLKR (SA-NLKR) is applied to the multiview image denoising problem and the effectiveness of the proposed algorithm is illustrated by experimental results.
Keywords :
"Noise reduction","Bandwidth","Graphics processing units","Robustness","MATLAB","Kernel","Image restoration"
Conference_Titel :
TENCON 2015 - 2015 IEEE Region 10 Conference
Print_ISBN :
978-1-4799-8639-2
Electronic_ISBN :
2159-3450
DOI :
10.1109/TENCON.2015.7372798