Preconditioning regularized least squares problems arising from high-resolution image reconstruction from low-resolution frames Original Research Article

In this paper, we study the problem of reconstructing a high-resolution image from multiple undersampled, shifted, degraded frames with subpixel displacement errors from multisensors. Preconditioned conjugate gradient methods with cosine transform based preconditioners and incomplete factorization based preconditioners are applied to solve this image reconstruction problem. Numerical examples are given to demonstrate the efficiency of these preconditioners. We find that cosine transform based preconditioners are effective when the number of shifted low-resolution frames are large, but are less effective when the number is small. However, incomplete factorization based preconditioners work quite well independent of the number of shifted low-resolution frames.