Total Variation (TV) methods are very e ective for recovering \blocky", possibly discontinuous, images from noisy data. A xed point algorithm for minimizing a TV-penalized least squares functional is presented and compared with existing minimization schemes. A variant of the cell-centered nite di erence 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

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... rithm is applied to actual data obtained from confocal microscopy.