A Fast, Robust Algorithm for Total Variation Based Reconstruction of Noisy, Blurred Images

| Tikhonov regularization with a modiied total variation regularization functional is used to recover an image from noisy, blurred data. This approach is appropriate for image processing in that it does not place a priori smoothness conditions on the solution image. An eecient algorithm is presented for the discretized problem which combines a xed point iteration to handle nonlinearity with an eeective preconditioned conjugate gradient iteration for large linear systems. Reconstructions and convergence results are presented for an application to satellite image reconstruction.

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