High-resolution image reconstruction refers to reconstructing high-resolution images from multiple low-resolution, shifted, degraded samples of a true image. The classical Tikhonov regularization is used in the reconstruction process. In this talk, we analyze this problem from the wavelet point of view. The numerical results show that the reconstructed images from our proposed wavelet algorithms are better than that from the Tikhonov least squares approach.