For spectral matting,the components are not compact enough.It′s hard to distinguish the foreground components from the background components without heuristic prior.Therefore,this paper presents an unsupervised matting method wit h visual attention prior.Based on the sorted radial-difference texture operator,the joint color and texture features are abstracted.The features are clustered to obtain the initial components whose dimensions are reduced previously.Taking adv antage of the human visual attention prior, the component′s center prior,boundary prior and saliency are calculated.Then th e foreground and background possibilities of the components are calculated.Based on the foreground and background possibilit ies,a coarse matte with the lowest matting cost is obtained.Finally,the coarse matte is optimized using the visual prior in formation and laplacian local information.The results reveal that the proposed algorithm has better integrity and detail prese rving ability.