A robustized vector recursive stabilizer algorithm for image restoration

The ill-posed problem of object reconstruction (or band-limited extrapolation) is reformulated in the framework of the general linear model in new recursive parametric forms. The resultant algorithms are shown to be natural stabilizers of the inherent instabilities of both the iterative and noniterative reconstruction/band-limited extrapolation methods. Both robustized and unrobustized versions of the algorithms are given. The recursive algorithms provide immunity to measurement noise outliers in burst noise of high variance. Unlike procedures suggested previously, these methods eliminate the need for stopping rule constraints and ensure convergence of the algorithms. The recursive formulation of the noniterative method of band-limited extrapolation is also found to be adaptable to multidimensional image restoration. Computer simulations verify the theory and demonstrate the computational efficiency of the method

Robust recursive estimation in the presence of heavy-tailed observation noise

Includes bibliographical references (p. 33-41).Supported by the U.S. Army Research Office fellowship. ARO-DAAL03-86-G-0017 Supported by the U.S. Air Force Office of Scientific Research. AFOSR-85-0227 AFOSR-89-0276Irvin C. Schick and Sanjoy K. Mitter

Robust Techniques for Signal Processing: A Survey

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryU.S. Army Research Office / DAAG29-81-K-0062U.S. Air Force Office of Scientific Research / AFOSR 82-0022Joint Services Electronics Program / N00014-84-C-0149National Science Foundation / ECS-82-12080U.S. Office of Naval Research / N00014-80-K-0945 and N00014-81-K-001