A saliency prediction model on 360 degree images using color dictionary based sparse representation

In this paper, a model using color dictionary based sparse representation for 360 degrees image saliency prediction is proposed, referred to as CDSR. The proposed model simulates human color perception, extracting the image features by color dictionary based sparse representation, combining with weighted center surround differences between image patches. Additionally, the partitioning operation, and latitude-bias enhancement are integrated into the proposed model to adapt for 360 degrees image saliency prediction. Experimental results on both natural images and 360 degrees images show the superior performances of the proposed saliency prediction model.