NDLI: Spatially-adaptive regularized super-resolution image reconstruction using a gradient-based saliency measure

Content Provider	IEEE Xplore Digital Library
Author	Zhenyu Liu Jing Tian Li Chen Yongtao Wang
Copyright Year	2011
Description	Author affiliation: School of Computer Science and Technology, Wuhan University of Science and Technology, China, 430081 (Zhenyu Liu; Jing Tian; Li Chen) \|\| Institute of Computer Science & Technology of Peking University, Beijing, China, 100871 (Yongtao Wang)
Abstract	This paper addresses the super-resolution image reconstruction problem with the aim to produce a higher-resolution image based on its low-resolution counterparts. The proposed approach adaptively adjusts the degree of regularization using the saliency measure of the local content of the image. This is in contrast to that a spatially-invariant regularization is used for the whole image in conventional approaches. Furthermore, a gradient-based assessment criterion is proposed to measure the saliency of the image. Experiments are conducted to demonstrate the superior performance of the proposed approach.
Starting Page	86
Ending Page	89
File Size	697809
Page Count	4
File Format	PDF
ISBN	9781457701221
e-ISBN	9781457701214
DOI	10.1109/ACPR.2011.6166567
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-28
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Strontium Educational institutions Spatial resolution Image reconstruction Signal resolution
Content Type	Text
Resource Type	Article

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