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Bottom-Up Saliency Estimation Based on Redundancy Reduction and Global Contrast |
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| Authors: | Miao Xiaodong Li Shunming Shen Huan Li Aiting |
| Institution: | 1. College of Mechanical and Power Engineering, Nanjing University of Technology, Nanjing, 210009, P.R.China 2. College of Power and Energy, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P.R.China 3. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, P.R.China |
| Abstract: | A new algorithm for bottom-up saliency estimation is proposed.Based on the sparse coding model,a power spectral filter is proposed to eliminate the second-order residual correlation,which suppresses the global repeated items effectively.In addition,aiming at modeling the mechanism of the human retina prior response to high-contrast stimuli,the effect of color context is considered.Experiments on the three publicly available databases and some psychophysical images show that the proposed model is comparable with the state-of-the-art saliency models,which not only highlights the salient objects in a complex environment but also pops up them uniformly. |
| Keywords: | redundancy reduction global contrast saliency bottom-up sparse coding |
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