Considering the feature of buildings in high resolution Synthetic Aperture Radar(SAR) images, an algorithm for extracting buildings from SAR image based on multi-scale information fusion is proposed. Taking the Non-Subsampled Contourlet Transform(NSCT) as multi-scale analysis framework, a multi-scale fusion segmentation method is proposed to extract the potential building regions. An edge detection method based on multi-scale data fusion is designed to extract the edge information. The results of multi-scale fusion segmentation and edge detection are combined to filter the false alarm and add the missing buildings. Experimental results show that the proposed method achieves better performance than the building detection algorithm based on feature fusion, and the average recall ratio reached 94% in the experimental images. These results prove the efficiency of the proposed approach.