Saliency Based on Multi-scale Ratio of Dissimilarity

Recently, many vision applications tend to utilize saliency maps derived from input images to guide them to focus on processing salient regions in images. In this paper, we propose a simple and effective method to quantify the saliency for each pixel in images. Specially, we define the saliency for a pixel in a ratio form, where the numerator measures the number of dissimilar pixels in its center-surround and the denominator measures the total number of pixels in its center-surround. The final saliency is obtained by combining these ratios of dissimilarity over multiple scales. For images, the saliency map generated by our method not only has a high quality in resolution also looks more reasonable. Finally, we apply our saliency map to extract the salient regions in images, and compare the performance with some state-of-the-art methods over an established ground-truth which contains 1000 images.