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Single-frame image super-resolution using learned wavelet coefficients

DSpace at IIT Bombay

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Title Single-frame image super-resolution using learned wavelet coefficients
 
Creator JIJI, CV
JOSHI, MV
CHAUDHURI, S
 
Subject high-resolution image
reconstruction algorithm
blur
registration
multisensors
restoration
limits
motion
noisy
super-resolution
wavelet decomposition
regularization
image restoration
 
Description We propose a single-frame, learning-based super-resolution restoration technique by using the wavelet domain to define a constraint on the solution. Wavelet coefficients at finer scales of the unknown high-resolution image are learned from a set of high-resolution training images and the learned image in the wavelet domain is used for further regularization while super-resolving the picture. We use an appropriate smoothness prior with discontinuity preservation in addition to the wavelet-based constraint to estimate the super-resolved image. The smoothness term ensures the spatial correlation among the pixels, whereas the learning term chooses the best edges from the training set. Because this amounts to extrapolating the high-frequency components, the proposed method does not suffer from oversmoothing effects. The results demonstrate the effectiveness of the proposed approach. (C) 2004 .
 
Publisher JOHN WILEY & SONS INC
 
Date 2011-08-16T14:14:09Z
2011-12-26T12:54:58Z
2011-12-27T05:43:27Z
2011-08-16T14:14:09Z
2011-12-26T12:54:58Z
2011-12-27T05:43:27Z
2004
 
Type Article
 
Identifier INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 14(3), 105-112
0899-9457
http://dx.doi.org/10.1002/ima.20013
http://dspace.library.iitb.ac.in/xmlui/handle/10054/9523
http://hdl.handle.net/10054/9523
 
Language en