by C. R. Vogel, M. E. Oman
SIAM J. Sci. Comput
http://www.math.montana.edu/~vogel/Papers/denoise.ps.gz
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Abstract:
Abstract. Total Variation (TV) methods are very effective for recovering "blocky", possibly discontinuous, images from noisy data. A fixed point algorithm for minimizing a TV-penalized least squares functional is presented and compared with existing minimization schemes. A variant of the cell-centered finite difference multigrid method of Ewing and Shen is implemented for solving the (large, sparse) linear subproblems. Numerical results are presented for one- and two-dimensional examples; in particular, the algorithm is applied to actual data obtained from confocal microscopy. Key words. Total Variation, denoising, image reconstruction, multigrid methods, confocal microscopy,
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