A Background Prior Based Saliency Detection for JPEG Image
Xiaolong Sun, Zhanghui Liu, Wenzhong Guo · 2014
Image saliency detection, which is aiming at locating meaningful objects in image and extracting the corresponding saliency map, has been attracting considerable attention. Most of existing saliency detection algorithms are dealing with uncompressed images, while numerous images are distributed and stored in JPEG format over Internet. Thus, this paper proposes a novel image saliency detection method dealing with JPEG images, which directly extracts 3 image low-level features (intensity, texture and color) from JPEG DCT blocks and then evaluates image saliency by calculating the shortest path from each internal point to the background. We compare our method with some state-of-the-art methods on the publicly available dataset MSRA-1000. Experimental results show that our method exhibits better performance in terms of all four evaluations than some state-of-the-art methods in our experiments. The final saliency maps indicate that our method can also produce satisfied saliency maps directly in compressed domain.