A computationally efficient superresolution image reconstruction algorithm
Superresolution reconstruction produces a high-resolution image from a set of low-resolution images. Previous iterative methods for superresolution [9], [1], [18], [27], [30] had not adequately addressed the computational and numerical issues for this ill-conditioned and typically underdetermined large scale problem, We propose efficient block circulant preconditioners for solving the Tikhonov-regularized superresolution problem by the conjugate gradient method. We also extend to underdetermined systems the derivation of the generalized cross-validation method for automatic calculation of regularization parameters, Effectiveness of our preconditioners and regularization techniques is demonstrated with superresolution results for a simulated sequence and a forward looking infrared (FLIR) camera image sequence.
superresolution circulant preconditioners underdetermined systems generalized cross-validation