Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/44034
Title: Single-image super-resolution using iterative Wiener filter based on nonlocal means
Authors: Hung, KW
Siu, WC 
Keywords: Iterative wiener filter
Nonlocal means filter
Super-resolution reconstruction
Issue Date: 2015
Publisher: Elsevier
Source: Signal processing. Image communication, 2015, v. 39, p. 26-45 How to cite?
Journal: Signal processing. Image communication 
Abstract: In this paper, we propose a single-frame super-resolution algorithm using a finite impulse response (FIR) Wiener-filter, where the correlation matrices are estimated using the nonlocal means filter. The major contribution of this work is to make use of the nonlocal means-based FIR Wiener filter to form a new iterative framework which alternately improves the estimated correlation and the estimated high-resolution (HR) image. To minimize the mean squared error of the estimated HR image, we have tried to optimize several parameters empirically, including the hyper-parameters of the nonlocal means filter by using an efficient offline training process. Experimental results show that the trained iterative framework performs better than the state-of-the-art algorithms using sparse representations and Gaussian process regression in terms of PSNR and SSIM values on a set of commonly used standard testing images. The proposed framework can be directly applied to other image processing tasks, such as denoising and restoration, and content-specific tasks such as face super-resolution.
URI: http://hdl.handle.net/10397/44034
ISSN: 0923-5965
DOI: 10.1016/j.image.2015.07.003
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

5
Last Week
0
Last month
Citations as of Aug 21, 2017

WEB OF SCIENCETM
Citations

4
Last Week
0
Last month
Citations as of Aug 20, 2017

Page view(s)

27
Last Week
0
Last month
Checked on Aug 20, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.