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Author (up) Thanh Ha Do; Salvatore Tabbone; Oriol Ramos Terrades edit  doi
isbn  openurl
  Title Document noise removal using sparse representations over learned dictionary Type Conference Article
  Year 2013 Publication Symposium on Document engineering Abbreviated Journal  
  Volume Issue Pages 161-168  
  Abstract best paper award
In this paper, we propose an algorithm for denoising document images using sparse representations. Following a training set, this algorithm is able to learn the main document characteristics and also, the kind of noise included into the documents. In this perspective, we propose to model the noise energy based on the normalized cross-correlation between pairs of noisy and non-noisy documents. Experimental
results on several datasets demonstrate the robustness of our method compared with the state-of-the-art.
  Address Barcelona; October 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-1-4503-1789-4 Medium  
  Area Expedition Conference ACM-DocEng  
  Notes DAG; 600.061 Approved no  
  Call Number Admin @ si @ DTR2013a Serial 2330  
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