DocumentCode :
3295084
Title :
RFSIM: A feature based image quality assessment metric using Riesz transforms
Author :
Zhang, Lin ; Zhang, Lei ; Mou, Xuanqin
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
321
Lastpage :
324
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.
Keywords :
computer vision; transforms; IQA model; RFSIM; Riesz transforms; computational models; feature based image quality assessment metric; feature similarity metric; human vision system; similarity index; Computational modeling; Feature extraction; Image quality; Indexes; Measurement; Transforms; Image quality assessment; Riesz transform; monogenic signal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5649275
Filename :
5649275
Link To Document :
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