Saliency can be described as the ability of an item to be detected from its background in any particular scene, and it aims to\nestimate the probable location of the salient objects. Due to the salient map that computed by local contrast features can extract\nand highlight the edge parts including painting lines of Flying Apsaras, in this paper, we proposed an improved approach based on\na frequency-tuned method for visual saliency detection of Flying Apsaras in the Dunhuang Grotto Murals, China. This improved\nsaliency detection approach comprises three important steps: (1) image color and gray channel decomposition; (2) gray feature\nvalue computation and color channel convolution; (3) visual saliency definition based on normalization of previous visual saliency\nand spatial attention function. Unlike existing approaches that rely on many complex image features, this proposed approach only\nused local contrast and spatial attention information to simulate human�s visual attention stimuli. This improved approach resulted\nin a much more efficient salient map in the aspect of computing performance. Furthermore, experimental results on the dataset of\nFlying Apsaras in the Dunhuang GrottoMurals showed that the proposed visual saliency detection approach is very effective when\ncompared with five other state-of-the-art approaches.
Loading....