Abstract
In this paper we investigate if the Difference of Gaussians model is able to predict observers perceived difference in relation to compression artifacts. A new image difference metric for specifically designed for compression artifacts is proposed. In order to evaluate this new metric a psychophysical experiment is carried out, where a dataset of 80 compressed JPEG and JPEG2000 images were generated from 10 different scenes. The results of the psychophysical experiment with 18 observers and the quality scores obtained from a large number of image difference metrics are presented.
Furthermore, a quantitative study based on a number of image difference metrics and five additional databases is performed in order to reveal the potential of the proposed metric. The analyses show that the proposed metric and most of the tested ones do not correlate well with the subjective test results, and thus the increased complexity of the recent metrics is not justified.
Keywords
- Human Visual System
- Psychophysical Experiment
- High Dynamic Range Image
- Just Noticeable Distortion
- Image Quality Metrics
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Simone, G., Caracciolo, V., Pedersen, M., Cheikh, F.A. (2010). Evaluation of a Difference of Gaussians Based Image Difference Metric in Relation to Perceived Compression Artifacts. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_48
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DOI: https://doi.org/10.1007/978-3-642-17274-8_48
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