Aiming at the disadvantages of large computational complexity and bad judgment of infrared low rank patch model,a more efficient multi-scale local low rank decomposition detection algorithm for infrared small targets is proposed.Firstly,the method uses the nonsubsampled pyramid transform to perform multi-scale decomposition on the infrared small target image.Secondly,the decomposed high-frequency sub-bands are fused,and the high-frequency information is extracted to extract the region of interest.Thirdly,the non-local autocorrelation property of the small target background is used to divide the region of interest and rearranges the blocks to form a new matrix.Finally,the matrix is decomposed into low rank to extract infrared small targets.Compared with other low rank decomposition methods,the proposed algorithm has better extraction performance and faster speed.The simulation results also prove its superiority and effectiveness.