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Fast, robust total variation-based reconstruction of noisy, blurred images

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2 Author(s)
C. R. Vogel ; Dept. of Math. Sci., Montana State Univ., Bozeman, MT, USA ; M. E. Oman

Tikhonov regularization with a modified 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 efficient algorithm is presented for the discretized problem that combines a fixed point iteration to handle nonlinearity with a new, effective preconditioned conjugate gradient iteration for large linear systems. Reconstructions, convergence results, and a direct comparison with a fast linear solver are presented for a satellite image reconstruction application

Published in:

IEEE Transactions on Image Processing  (Volume:7 ,  Issue: 6 )