Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/20652
Title: RFSIM : a feature based image quality assessment metric using Riesz transforms
Authors: Zhang, L
Zhang, L 
Mou, X
Keywords: Image quality assessment
Riesz transform
Monogenic signal
Issue Date: 2010
Publisher: IEEE
Source: 2010 17th IEEE International Conference on Image Processing (ICIP), 26-29 September 2010, Hong Kong, p. 321-324 How to cite?
Abstract: Image quality assessment (IQA) aims to provide computational models to measure the image quality in a perceptually consistent manner. In this paper, a novel feature based IQA model, namely Riesz-transform based Feature SIMilarity metric (RFSIM), is proposed based on the fact that the human vision system (HVS) perceives an image mainly according to its low-level features. The 1st-order and 2nd-order Riesz transform coefficients of the image are taken as image features, while a feature mask is defined as the edge locations of the image. The similarity index between the reference and distorted images is measured by comparing the two feature maps at key locations marked by the feature mask. Extensive experiments on the comprehensive TID2008 database indicate that the proposed RFSIM metric is more consistent with the subjective evaluation than all the other competing methods evaluated.
URI: http://hdl.handle.net/10397/20652
ISBN: 978-1-4244-7992-4
978-1-4244-7993-1 (E-ISBN)
ISSN: 1522-4880
DOI: 10.1109/ICIP.2010.5649275
Appears in Collections:Conference Paper

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

SCOPUSTM   
Citations

67
Last Week
31
Last month
Citations as of Oct 18, 2017

WEB OF SCIENCETM
Citations

43
Last Week
0
Last month
0
Citations as of Oct 13, 2017

Page view(s)

80
Last Week
5
Last month
Checked on Oct 16, 2017

Google ScholarTM

Check

Altmetric



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