In recent years a number of different vision models have been proposed to assist in the evaluation of image quality. However, there have been few attempts to independently evaluate these models and to make comparisons between them. In this paper we first summarize the work that has been done in image quality modeling. We then select two of the leading image quality models, the Daly Visible Differences Predictor and the Sarnoff Visual Discrimination Model, for further study. We begin by describing our implementation, which was done from the published papers, of each of the models. We next discuss the similarities and the differences between the two models. The paper ends with a summary of the important advantages of each approach. The comparison of these two models is presented in the context of our research interests which are image quality evaluation for both computer imaging and computer graphics tasks. The paper includes illustrations drawn from these two areas.
|Original language||English (US)|
|Number of pages||12|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Jul 17 1998|
|Event||Human Vision and Electronic Imaging III 1998 - San Jose, United States|
Duration: Jan 24 1998 → Jan 30 1998
Bibliographical noteFunding Information:
Primary funding for this work was provided by Xerox Corporation with additional support from the National Science Foundation under grant number CCR-9619967.
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