Inverse Bilateral Filter for Saliency

The analysis and automatic detection of visual salient image regions has been the subject of considerable research useful in object segmentation, adaptive compression and re-targeting. However, the nature of the essential mechanisms intervening human visual saliency remains elusive. To assess the validity of salient regions some kind of prior model is consistently required. This paper proposes a new model using inverse bilateral fitter that allows the system to output saliency maps with salient objects in their context. The filter is described firstly for automatically learning local contrast distribution to accurately predict salient image regions. Along with the contrast distribution checking, local opposition is analyzed by the second application of the inverse bilateral filter to establish fuzzy boundary of salient regions in form of trimap. This approach is shown to increase the reliability of identifying visual salient objects. Output from the research has potential applications in the areas of object detection and recognition.