A rate unknown image steganalysis scheme is proposed based on multiple classifier fusion. Firstly, various classified results are acquired by using the multi-rate classifiers established in the training phase. Secondly, these classified results are converted to evidence and enhanced through introducing weighted coefficients which are acquired according to the missed detection rates and the false alarm rates of different classifiers. Finally, the decision is obtained by Dempster-Shafer(D-S) evidence theory based on weighted coefficients. The detection work is presented to attack LSB matching. Experimental results show that the proposed method improves detection accuracy.