Shadow detection and removal based on the saliency map
Zhiwen Fang, Zhiguo Cao, Chunhua Deng, Ruicheng Yan, Yueming Qin · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
The detection of shadow is the first step to reduce the imaging effect that is caused by the interactions of the light source with surfaces, and then shadow removal can recover the vein information from the dark region. In this paper, we have presented a new method to detect the shadow in a single nature image with the saliency map and to remove the shadow. Firstly, RGB image is transferred to 2D module in order to improve the blue component. Secondly, saliency map of blue component is extracted via graph-based manifold ranking. Then the edge of the shadow can be detected in order to recover the transitional region between the shadow and non-shadow region. Finally, shadow is compensated by enhancing the image in RGB space. Experimental results show the effectiveness of the proposed method.