M.M. Cheng, G.X. Zhang, N.J. Mitra, X. Huang, S.M. Hu
CVPR, volume 37, issue 3, pp. 569-582, (2011)
Reliable estimation of visual saliency allows appropriate processing of
images without prior knowledge of their contents, and thus remains an
important step in many computer vision tasks including image
segmentation, object recognition, and adaptive compression. We propose a
regional contrast based saliency extraction algorithm, which
simultaneously evaluates global contrast differences and spatial
coherence. The proposed algorithm is simple, efficient, and yields full
resolution saliency maps. Our algorithm consistently outperformed
existing saliency detection methods, yielding higher precision and
better recall rates, when evaluated using one of the largest publicly
available data sets. We also demonstrate how the extracted saliency map
can be used to create high quality segmentation masks for subsequent
image processing.