@inproceedings{87730844c84c44df9a46d2b230615922,
title = "Systematic evaluation of super-resolution using classification",
abstract = "Currently two evaluation methods of super-resolution (SR) techniques prevail: The objective Peak Signal to Noise Ratio (PSNR) and a qualitative measure based on manual visual inspection. Both of these methods are sub-optimal: The latter does not scale well to large numbers of images, while the former does not necessarily reflect the perceived visual quality. We address these issues in this paper and propose an evaluation method based on image classification. We show that perceptual image quality measures like structural similarity are not suitable for evaluation of SR methods. On the other hand a systematic evaluation using large datasets of thousands of real-world images provides a consistent comparison of SR algorithms that corresponds to perceived visual quality. We verify the success of our approach by presenting an evaluation of three recent super-resolution algorithms on standard image classification datasets.",
author = "Namboodiri, {Vinay P.} and {De Smet}, Vincent and {Van Gool}, Luc",
year = "2011",
month = dec,
day = "29",
doi = "10.1109/VCIP.2011.6115959",
language = "English",
isbn = "9781457713200",
series = "2011 IEEE Visual Communications and Image Processing, VCIP 2011",
publisher = "IEEE",
booktitle = "2011 IEEE Visual Communications and Image Processing, VCIP 2011",
address = "USA United States",
note = "2011 IEEE Visual Communications and Image Processing, VCIP 2011 ; Conference date: 06-11-2011 Through 09-11-2011",
}