Saliency detection using quatemionic distance based weber descriptor and object cues

In this paper, a simple and efficient method, based on Quaternionic Distance Based Weber Descriptor (QDWD) and object cues, is proposed for saliency detection. Firstly, QDWD, which was initially designed for detecting outliers in color images, is used to represent the directional cues in an image. Meanwhile, two low-level priors, namely the color contrast and center cue of the image, are utilized and fused as an object-level cue. Finally, by combining QDWD with object cues, a reliable saliency map of the image can be computed. Experimental results, based on a widely used and openly available database, show that the proposed method is able to produce promising results, compared to other state-of-the-art saliency-detection models.