To solve the fault segmentation of the mean shift segmentation algorithm based on the fixed space and color bandwidth, a mean-shift segmentation algorithm based on the density revise with saliency feature was proposed. A region saliency computing method was firstly proposed on the basis of density estimation of main color quantization. Secondly, region saliency was fused with pixel level saliency as density modifying factor, and the fused image was modified as input for mean-shift segmentation. Finally, the scatter regions were merged to obtain the final segmentation results. The experimental results show that for the truth boundaries, the average precision and recall of the proposed segmentation algorithm are 0.64 and 0.78 in 4 scales. Compared with other methods, the accuracy of the proposed segmentation method is significantly improved. It can effectively improve the integrity of the target and the robustness of natural color image segmentation.