Perceptually meaningful quadtree decomposition using dual-homogeneous criteria
Saliency detection is a powerful tool for many applications because it can provide valuable information reflecting human visual attention. Quadtree decomposition is a classical and efficient image operator which can divide image into square blocks in different scales. The blocks in smaller size contain valuable information such as edges and texture. In image lossy compression or similar applications, we want to reserve valuable regions (salient objects) as much as we can, meanwhile, we also want to suppress non-salient regions human are not interested in. For these reasons, we propose an ingenious saliency guided quadtree decomposition model. The proposed model outperforms traditional methods in two aspects: It reserves the salient regions well, and the edges can be protected simultaneously.