DocumentCode :
232802
Title :
An adaptive regularization image super-resolution reconstruction algorithm
Author :
Zhao Xiao-qiang ; Jia Yun-xia
Author_Institution :
Coll. of Electr. & Inf. Eng., Lanzhou Univ. of Tech., Lanzhou, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
7258
Lastpage :
7262
Abstract :
Because of the traditional regularization parameters in the regularization method is fixed, in reconstruction images are not good to keep details such as image edge and texture information.In view of these shortcomings is proposed in this paper a bilateral total variation based on adaptive regularization image super-resolution algorithm, through changing regularized parameter to control the data fidelity term in the objective function and the proportion of regularization.Experimental results show that compared with the traditional reconstruction method in this paper, the method to the determination of adaptive regularization parameter, find the optimal solution, and in the region of the edge and texture details such as embodies better reconstruction effect.
Keywords :
image reconstruction; image resolution; image texture; adaptive regularization image; adaptive regularization parameter; bilateral total variation; data fidelity term; image edge information; image super-resolution reconstruction algorithm; image texture information; objective function; reconstruction effect; regularization method; regularization parameters; Electronic mail; Image edge detection; Image reconstruction; Image resolution; Image restoration; Reconstruction algorithms; TV; adaptive regularization; bilateral total variational; super-resolution reconstruction; to keep edge;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6896202
Filename :
6896202
Link To Document :
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