%0 Journal Article %T DSD: document sparse-based denoising algorithm %A Thanh Ha Do %A Oriol Ramos Terrades %A Salvatore Tabbone %J Pattern Analysis and Applications %D 2019 %V 22 %N 1 %F Thanh Ha Do2019 %O DAG; 600.097; 600.140; 600.121 %O exported from refbase (http://refbase.cvc.uab.es/show.php?record=3254), last updated on Tue, 24 Nov 2020 10:23:37 +0100 %X 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. %K Document denoising %K Sparse representations %K Sparse dictionary learning %K Document degradation models %U https://link.springer.com/article/10.1007/s10044-018-0714-3 %P 177–186