Retrieving images combining saliency detection with IRM

The research from cognitive psychology and neurobiology suggests that people have a strong ability to perceive objects before identifying them, and the human vision system (HVS) processes some salient regions of an image while leaving others nearly unprocessed. Based on this observation, we assume people prefer to pay more attention to salient regions when judging whether images are matched. A novel saliency detection based on reconstruction residual is proposed to calculate saliency maps and generate salient regions, which helps decrease the interference from irrelevant regions in image retrieval. The introduction of integrated region matching (IRM) can better characterize the spatial constraints among salient regions to conduct similarity measurement. The experimental results demonstrate that the proposed saliency detection has a good performance. At the same time, the combination of salient regions and IRM can help improve the state-of-the-art retrieval algorithms.