A Saliency Detection Technique Considering Self- and Mutual-Information

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In this paper, we present a novel approach to saliency detection. We define a visually salient region in an image with following two properties; global spatial redundancy, i.e., mutual-information, and local saliency, i.e., self-information or simply the region complexity. The former is its probability of occurrence within the image, whereas the latter defines how much information is contained within a region, and it is quantified by the entropy. By combining the global spatial redundancy measure and local entropy, we can achieve a simple, yet robust saliency detector. We evaluate it quantitatively and qualitatively. The comparison to Itti et al. [6], the spectral residual approach by Hou and Zhang [5], Achanta et al. [13] as well as to Zhai and Shah [14], on publicly available data shows a significant improvement.

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