Propagation-based methods have attracted more and more attention in saliency detection. We present a propagation-based saliency detection framework to overcome some drawbacks in existing methods. First, we construct an effective background-based map by defining a method to remove foreground noises in image boundaries. Second, a saliency propagation method is proposed to further refine the background-based map by introducing a feedback regulation mechanism into saliency propagation. Finally, an optimization method is developed to further enhance the contrast between salient object and background. Extensive experiments on five benchmark datasets are carried out, and experimental results show the superiority of the proposed method than other state-of-the-art methods.