ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:TP-P5.6
Session:Image/Video Restoration and Enhancement
Time:Tuesday, October 10, 14:20 - 17:00
Presentation: Poster
Topic: Image & Video Restoration and Enhancement: Multiframe image restoration
Title: QUALITY ASSESSMENT FOR SUPER-RESOLUTION IMAGE ENHANCEMENT
Authors: Amy Reibman; AT&T Labs - Research 
 Robert M. Bell; AT&T Labs - Research 
 Sharon Gray; AT&T Labs - Research 
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.