TY  - CONF
AU  - Thanh Ha Do
AU  - Salvatore Tabbone
AU  - Oriol Ramos Terrades
A2  - ACM-DocEng
PY  - 2013//
TI  - Document noise removal using sparse representations over learned dictionary
BT  - Symposium on Document engineering
SP  - 161
EP  - 168
N2  - 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.
SN  - 978-1-4503-1789-4
UR  - http://dx.doi.org/10.1145/2494266.2494281
N1  - DAG; 600.061
ID  - Thanh Ha Do2013
ER  -