Adaptive local context suppression of multiple cues for salient visual attention detection

Visual attention is obtained through determination of contrasts of low level features or attention cites like intensity, color etc. We propose a new texture attention cite that is shown to be more effective for images where the salient object regions and background have similar visual characteristics. Current visual attention models do not consider local contextual information to highlight attention regions. We also propose a feature combination strategy by suppressing saliency based on. context information that is effective in determining the trite attention region. We compare our approach with other visual attention models using a novel Average Discrimination Ratio measure.