High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting (The Morgan Kaufmann Series in Computer Graphics)
Measuring perceptual contrast in digital images
Journal of Visual Communication and Image Representation
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Full-Reference Image Quality Metrics: Classification and Evaluation
Foundations and Trends® in Computer Graphics and Vision
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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.