PT Unknown
AU Thanh Ha Do
   Salvatore Tabbone
   Oriol Ramos Terrades
TI Document noise removal using sparse representations over learned dictionary
BT Symposium on Document engineering
PY 2013
BP 161
EP 168
DI 10.1145/2494266.2494281
AB best paper awardIn 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. Experimentalresults on several datasets demonstrate the robustness of our method compared with the state-of-the-art.
ER