Research on Visual Saliency Model Based on CovSal Algorithm and Histogram Contrast

Abstract

This paper proposes a novel visual saliency model based on the CovSal algorithm of the region covariance matrices and histogram contrast (HC) method. First, we give a new CovSal algorithm of the local saliency contrast by improving the center-surrounder segmentation method. Second, we add the HC algorithm of the global saliency contrast, and then we sparsify the global saliency map using the low-rank matrix. Finally, we integrate the local and global saliency maps through combining both the CovSal and HC contrast. Present paper proposes a new visual saliency model that combines the local and global saliency contrast algorithms, simultaneously retaining their advantages and eliminating their drawbacks. For example, the proposed model reduces the influence of background and texture details. The experimental results show that the performance of the visual saliency model proposed in this paper has been improved compared to the CovSal algorithm presented by Erdem and Erdem.