For the poor performance of dim and small infrared target detection under complex background, a novel target detection algorithm inspired by the anisotropic diffusion equation and the multi-scale analysis was presented. Firstly, the raw target image is decomposed by the surfacelet transform into multi-scale and mutli-direction details characteristics. Then, the improved anisotropic diffusion equation difference filter and the local mean removal filter are adopted to refine the high-frequency and the low-frequency subbands respectively. Reconstruct the refined subbands by the inverse surfacelet transform to obtain the result image with target enhancement and background suppression. Finally, the classical adaptive threshold segmentation method is used to implement target detection. Various infrared images with dim and small targets are used to verify the efficiency of the algorithm. Compared with wavelet filter and anisotropic diffusion equation filter, the experimental results show that the proposed algorithm can effectively suppress the background and its edge, and acquires a better performance of the target detection.