A Fast and Effective Algorithm for a Poisson Denoising Model With Total Variation
In this letter, we present a fast and effective algorithm for solving the Poisson-modified total variation model proposed in [Le et al., "A variational approach to reconstructing images corrupted by Poisson noise," J. Math. Imag. Vis., vol. 27, no 3, pp. 257-263, Apr. 2007]. The existence...
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Veröffentlicht in: | IEEE signal processing letters 2017-03, Vol.24 (3), p.269-273 |
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Sprache: | eng |
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Zusammenfassung: | In this letter, we present a fast and effective algorithm for solving the Poisson-modified total variation model proposed in [Le et al., "A variational approach to reconstructing images corrupted by Poisson noise," J. Math. Imag. Vis., vol. 27, no 3, pp. 257-263, Apr. 2007]. The existence and uniqueness of solution for the model are proved by using a different method. A semi-implicit difference scheme is designed to discretize the derived gradient descent flow with a large time step. Different from the original numerical scheme, our scheme is conditional stable with a less stringent condition and can ensure that the numerical solution is strictly positive in image domain. Experimental results show the efficiency and effectiveness of our algorithm. |
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ISSN: | 1070-9908 1558-2361 |
DOI: | 10.1109/LSP.2017.2654480 |