DocumentCode
1571065
Title
Quality assessment for super-resolution image enhancement
Author
Reibman, Amy R. ; Bell, R.M. ; Gray, S.
fYear
2006
Firstpage
2017
Lastpage
2020
Abstract
A typical image formation model for super-resolution (SR) introduces blurring, aliasing, and added noise. The enhancement itself may also introduce ringing. In this paper, we use subjective tests to assess the visual quality of SR-enhanced images. We then examine how well some existing objective quality metrics can characterize the observed subjective quality. Even full-reference metrics like MSE and SSIM do not always capture visual quality of SR images with and without residual aliasing.
Keywords
image enhancement; image resolution; mean square error methods; MSE; SSIM; blurring; image enhancement; image formation model; mean square error; subjective testing; super-resolution; visual quality assessment; Frequency estimation; Image enhancement; Image quality; Image resolution; Image sampling; PSNR; Quality assessment; Spatial resolution; Strontium; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 2006 IEEE International Conference on
Conference_Location
Atlanta, GA
ISSN
1522-4880
Print_ISBN
1-4244-0480-0
Type
conf
DOI
10.1109/ICIP.2006.312895
Filename
4106955
Link To Document