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DSD: document sparse-based denoising algorithm

Abstract : In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising.
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https://hal.univ-lorraine.fr/hal-02965116
Contributor : Salvatore Tabbone <>
Submitted on : Tuesday, October 13, 2020 - 6:44:23 AM
Last modification on : Thursday, October 15, 2020 - 4:07:56 AM

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T. Do, O. Ramos Terrades, S. Tabbone. DSD: document sparse-based denoising algorithm. Pattern Analysis and Applications, Springer Verlag, 2019, 22 (1), pp.177-186. ⟨10.1007/s10044-018-0714-3⟩. ⟨hal-02965116⟩

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