A hierarchical visual saliency detection method by combining distinction and background probability maps

We propose a bottom-up method for image saliency detection by combining the distinction map and the background probability map. The contributions of our work are as follows. First, a novel distinction measure is proposed by weighted combination of the color contrast and the spatial distance distribution criterions in previous works. Second, a background pixel distribution approximation method using patches sampled near the image borders is introduced. Finally, the distinction map and the background probability map are incorporated into a hierarchical framework to generate the final saliency map. We have compared our method with several recent works experimentally and observe that competitive results can be achieved.