Color Feature Unified-Based Approach for Visual Fixation

Human visual attention can be deal with complex scenes in real time effortlessly and efficiently and detect the most interesting regions quickly. Based on the characteristic of human visual attention, one more comprehensive computation framework is proposed which fully takes the advantage of color contrast to obtain visual fixations of natural color images. Firstly, the color space conversion strategy is employed. The RGB color images are converted into the HSV color space and Lab color space respectively. Then, the superpixels generation algorithm is utilized to segment natural images in the HSV color space and in the Lab color space. Next, color feature-contrast in the two color space is respectively implemented and the corresponding single visual fixation is obtained. Finally, the color feature-fused strategy is adopted in order to get the final visual fixation. Experimental results show that our proposed framework can effectively improve the effect of visual fixations compared with a single color space for the natural color images. Moreover, the full resolution visual fixations can be obtained by employing the proposed framework in this paper compared to the context-aware approach. Meanwhile, these experimental results also clearly demonstrate that the proposed model for saliency estimation is effective.