Abstract
In this paper, computational methods are proposed to compute color edge saliency based on the information content of color edges. The computational methods are evaluated on bottom-up saliency in a psychophysical experiment, and on a more complex task of salient object detection in real-world images. The psychophysical experiment demonstrates the relevance of using information theory as a saliency processing model and that the proposed methods are significantly better in predicting color saliency (with a human-method correspondence up to 74.75% and an observer agreement of 86.8%) than state-of-the-art models. Furthermore, results from salient object detection confirm that an early fusion of color and contrast provide accurate performance to compute visual saliency with a hit rate up to 95.2%. © 2010 Optical Society of America.
Original language | English |
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Pages (from-to) | 613-621 |
Journal | Journal of the Optical Society of America A: Optics and Image Science, and Vision |
Volume | 27 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Mar 2010 |