Abstract: An image saliency analysis method based on the combination of grey relational computation and prior knowledge, which is a saliency computation and integration based on three different priori of boundary background, global color distribution and top salient information. The SLIC method segment the image into superpixels, then selecting the boundary superpixels on four image sides respectively to construct the reference sequence, and the same method used to construct the comparative sequence of the rest superpixels. Then four initial saliency images was derived based on boundary background priori through a grey relational computation, to make weighted and improved. Furtherly integrated the global color spatial distribution information and the top priori information to produce the final saliency image. An experiment were made on the open MSRA-1000 datasets and compared the results with several existing classic methods, conclusions shows the method has a better precision and recall, even under a more complex background.

Key words: image saliency, grey relational analysis, regional characteristics descriptor, prior knowledge