Visual Saliency Computing with Color Feature Integration Based on Psychological Experiment

Abstract

This paper introduced a method of visual saliency computing with color feature integration based on the psychological experiment. Firstly, based on the results of the psychological experiment of the saliency features, the color saliency features with the highest selected frequency were extracted. Then, the saliency map of each saliency feature was generated with the combination center “of-surround” theory from Itti model. Finally, the feature integration mechanism was adopted to combine each saliency feature to integrate the saliency map. The gray value of each pixel in the saliency map reflected the computing value of visual saliency. The results shows that the proposed method is highly sensitive to color and can effectively recognize the saliency objects of the color static images. In addition, when detecting the saliency objects from different types, it has a stable performance with the good generalization.