Abstract:
Image quality assessment is an important component in every image processing system where the last link of the chain is the human observer. This domain is of increasing i...Show MoreMetadata
Abstract:
Image quality assessment is an important component in every image processing system where the last link of the chain is the human observer. This domain is of increasing interest, in particular in the context of image compression where coding scheme optimization is based on the distortion measure. Many objective image quality measures have been proposed in the literature and validated by comparing them to the Mean Opinion Score (MOS). We propose in this paper an empirical study of several indicators and show how one can improve the performances by combining them. We learn a regularized regression model and apply variable selection techniques to automatically find the most relevant indicators. Our technique enhances the state of the art results on two publicly available databases.
Published in: Proceedings of the ITI 2009 31st International Conference on Information Technology Interfaces
Date of Conference: 22-25 June 2009
Date Added to IEEE Xplore: 07 August 2009
Print ISBN:978-953-7138-15-8
Print ISSN: 1330-1012