DocumentCode :
2934707
Title :
Image super-resolution reconstruction based on adaptive interpolation norm regularization
Author :
Han, Yubing ; Shu, Feng ; Zhang, Qingchuan
Author_Institution :
Nanjing Univ. of Sci. & Technol., Nanjing
fYear :
2007
fDate :
Nov. 28 2007-Dec. 1 2007
Firstpage :
698
Lastpage :
701
Abstract :
An image super-resolution reconstruction algorithm is proposed based on adaptive interpolation norm regularization, which can not only preserve more details near image edges than Tikhonov regularization, but also efficiently alleviate the staircasing of total variation regularization on flat regions. Furthermore, we propose the use of regularization functional instead of a constant regularization parameter. The regularization functional is defined in terms of the restored image at each iteration step, therefore allowing for the simultaneous determination of its value and the restoration of the degraded image. The iteration scheme, convergence and control function are thoroughly studied. Experimental results demonstrate the power of the proposed method.
Keywords :
image reconstruction; image resolution; iterative methods; Tikhonov regularization; adaptive interpolation norm regularization; constant regularization parameter; image edges; image super-resolution reconstruction; iteration scheme; Adaptive signal processing; Convergence; Equations; Image reconstruction; Image resolution; Image restoration; Interpolation; Reconstruction algorithms; Signal processing algorithms; Signal resolution; Euler-Lagrange equation; Super-resolution reconstruction; Tikhonov regularization; interpolation norm regularization; total variation regularization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Signal Processing and Communication Systems, 2007. ISPACS 2007. International Symposium on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-1447-5
Electronic_ISBN :
978-1-4244-1447-5
Type :
conf
DOI :
10.1109/ISPACS.2007.4445983
Filename :
4445983
Link To Document :
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