DocumentCode :
3758688
Title :
Total variation deblurring algorithm extension in third-order tensor space
Author :
Hong Liu;Benyong Liu
Author_Institution :
Institute of Intelligent Information Processing, Guizhou University, Guiyang, China
fYear :
2015
Firstpage :
221
Lastpage :
224
Abstract :
The deblurring algorithm based on the total variation (TV) model can better preserve sharp edges. However, the existing algorithms could not really deal with the multichannel images. In this paper, we extend the general TV model in matrix space to tensor TV model in third-order tensor space, called as t-TV model, utilizing a new tensor product, t-product. And an efficient algorithm, based on alternating minimization, is adopted to solve the t-TV model. The proposed method retains the advantages of the general TV regularization. Meanwhile it could directly deal with the multichannel images in tensor framework. Experimental results show that the proposed method can achieve satisfactory performance on gray and color blurred images.
Keywords :
"Decision support systems","Tensile stress","Image restoration","Image reconstruction","Deconvolution"
Publisher :
ieee
Conference_Titel :
Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2015 IEEE
Print_ISBN :
978-1-4799-1979-6
Type :
conf
DOI :
10.1109/IAEAC.2015.7428551
Filename :
7428551
Link To Document :
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