Aspect Ratio Similarity (ARS) for image retargeting quality assessment
Yabin Zhang, Weisi Lin, Xinfeng Zhang, Yuming Fang, Leida Li
Abstract
During the past few years, there have been various kinds of content-aware image retargeting methods proposed for image resizing. However, the lack of effective objective retargeting quality metric limits the further development of image retargeting. Different from the traditional image quality assessment, the quality degradation of the retargeted images is mainly caused by the geometric changes due to retargeting. In this paper, we propose a practical approach to reveal the geometric changes during image retargeting, and design an Aspect Ratio Similarity (ARS) metric to predict the visual quality of the retargeted image. The experimental results on the widely used dataset show that the proposed metric outperforms the state of the arts.
BibTeX
@inproceedings{icassp2016_aspectratiosimil,
title = {Aspect Ratio Similarity (ARS) for image retargeting quality assessment},
author = {Yabin Zhang and Weisi Lin and Xinfeng Zhang and Yuming Fang and Leida Li},
booktitle = {ICASSP 2016},
year = {2016}
}