Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34152
Title: An iterative super resolution algorithm based on adaptive FIR Wiener filtering
Authors: Zhang, KX
Chan, YH 
Siu, WC 
Issue Date: 2010
Source: APSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2010, p. 125-128 (CD) How to cite?
Abstract: Aiming at image/video super resolution applications, this paper presents a spatially adaptive FIR wiener filter for super resolution reconstruction. Missing high resolution samples can be estimated as the weighted sum of nearby low resolution samples. In the proposed algorithm, the optimal weighting coefficients for each of nearby low resolution samples are determined with a distance-based correlation model of samples and iteratively refined according to the most updated estimates of the missing high resolution samples. Both objective and subjective measurements in our simulations show that the proposed algorithm can produce a better result as compared with some conventional algorithms across different noise conditions.
Description: 2nd Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2010, Biopolis, 14-17 December 2010
URI: http://hdl.handle.net/10397/34152
Appears in Collections:Conference Paper

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