Abstract:

Based on Koch’s neural architecture and the philosophy of structural similarity, a novel visual salient region detection method is proposed. This method constructs a multifeature visual saliency model by using SSIM’s high abstraction for HVS, and it uses a new centersurround operator to measure the saliency degree of the natural images. The experimental results show that our method can detect the salient region effectively. In comparison to Itti’s method, our method overcomes the weakness of Mosaic caused by neighboring interpolation, and it shows better performance on contour detection and antinoise.

Key words: neural architecture;structural similarity;feature integration;saliency map