In order to fastly and batch detect the visual interestingness of clothing and accessory images, the bottom-to-top visual saliency detection method was utilized to describe the visual saliency based on human visual attention model. Firstly,the bottom characteristics including brightness, color and texture of fashion image were extracted to construct multiple feature channels. Besides, combining normalized method was used to filter the feature image. Finally, the constructed three feature maps were fused and the visual focus area and significant bright map layer were converged. In the experiment, the visual saliency of color blocks map, different texture fabric images, clothing and accessory images were detected. The results show that the proposed algorithm effectively and objectively extracts the salient region and presents the significant degree.