Research on image saliency detection algorithm based on edge information combined with spatial weight

Aiming at the problems that the current saliency detection algorithm generally has more background noise and the target area detection is not complete enough, a spatial domain saliency algorithm is proposed. Firstly, the input image is superpixel segmented, and the edge information is used as the background prior area set. By calculating the difference in color and brightness between the superpixel and the superpixel in the background prior area set, a significant background difference map is obtained. Then it is determined the foreground a priori area set, calculated the difference between each superpixel and the superpixel in the foreground a priori area set, and obtained a foreground difference saliency map. Finally, it is fused the two parts of the saliency map, builded a visual center on this basis, and determined the spatial weight information of each superpixel around the visual center to obtain the final saliency map. The MSRA-1000 database was used for a comparative experiment. The results show that the algorithm in this paper is more accurate and the overall effect is better..