A novel saliency map extraction method based on improved Itti´s model

To obtain a saliency map close to the saliency object as much as possible, an improved bottom-up visual attention model is presented. Firstly, early visual features such as intensity, color and orientation are extracted from an input image at multiple scales; Secondly, three conspicuity maps are created respectively according to early features; Thirdly, three conspicuity maps are combined into a saliency map nonlinearly. In the last step, different from Itti´s model, the contribution rate of each conspicuity map to the saliency map is done in inversely proportional to the saliency points area. A set of experiments were carried out to demonstrate the effectiveness of the proposed model. The experimental results show that the algorithm is effective and saliency map accuracy increased by 15-20% compared to Itti´s model.