Recursive implementation of total least squares algorithm for image reconstruction from noisy, undersampled multiframes

Abstract

It is shown how the total least squares recursive algorithm for the real data FIR (finite impulse response) adaptive filtering problem can be applied to reconstruct a high-resolution filtered image from undersampled, noisy multiframes, when the interframe displacements are not accurately known. This is done in the wavenumber domain after transforming the complex data problem to an equivalent real data problem, to which the algorithm developed by C.E. Davila (Proc. ICASSP 1991 p.1853-6 of 1991) applies. The procedure developed also applies when the multiframes are degraded by linear shift-invariant blurs. All the advantages of implementation via massively parallel computational architecture apply. The performance of the algorithm is verified by computer simulations.<>