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.
|Journal||Journal of the Optical Society of America A: Optics and Image Science, and Vision|
|Publication status||Published - 1 Mar 2010|
Vazquez, E., Gevers, T., Lucassen, M., Van de Weijer, J., & Baldrich, R. (2010). Saliency of color image derivatives: a comparison between computational models and human perception. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 27(3), 613-621. https://doi.org/10.1364/JOSAA.27.000613