Multilevel image reconstruction by interpolating wavelet coefficients

High resolution (HR) image reconstruction produces one high-resolved image from a set of low-resolution (LR) images which may be blurred, degraded and shifted. In this paper, a wavelet-based multilevel HR image reconstruction method is proposed to recover the HR image from the estimated middle-resolution (MR) data which are obtained from the observed LR images. The relationship between the wavelet subbands and the LR images is extensively investigated. Based on this relationship, an iterative balanced reconstruction with error correction approach is developed in the low-level reconstruction process to estimate the MR data from the LR images. The numerical experiments show that the proposed method outperforms the state of the art methods such as Tikhonov least-squares approach and Chan et al. Algorithm 3.