In order to improve the quality of infrared images while maintaining texture information to a greater extent, a multiscale analysis and weighted least squares method for stripe noise nonuniformity correction is proposed. The algorithm uses the weighted least squares method to smooth the image, applies the wavelet transform to extract the vertical component of the smooth image which is replaced with the vertical component of the original image subsequently, and reconstructs the corrected image by wavelet reconstruction. The proposed algorithm can accurately remove infrared noise without causing more troublesome "ghosting" problems. The proposed algorithm is experimented on multiple sets of different infrared image data, and compared with the stateoftheart destriping algorithms. The results show that the proposed algorithm has better visual effects and image quality evaluation parameters.