Visual Saliency Detection via Contrast Combinations

Saliency detection is an important task in computer vision and image processing. The most influential factor in bottom-up visual saliency is contrast operation. In this paper, we propose a unified model to combine widely used contrast measurements, namely, center-surround, corner-surround and global contrast to detect visual saliency. The proposed model benefits from the advantages of each individual contrast operation， and thus produces more robust and accurate saliency maps. Extensive experimental results on natural images show the effectiveness of the proposed model for visual saliency detection task, and demonstrate the combination is superior to individual subcomponent.