The periodic structure of the underlying support of paintings on canvas can become quite prominent and disturbing in high resolution digital recordings. In this paper, we construct a new model and method for the digital removal of canvas which is considered as a noise component superimposed on the painting artwork. The high resolution of the images prohibits the efficient application of existing adaptive denoising filters. Hence, a two-step approach is proposed. First a (smoothing) Wiener filter is applied to the complete image. The second step consists of a spatially adaptive extension with low-complexity to obtain a generic digital canvas removal filter.
Cornelis, B , Dooms, A , Cornelis, J & Schelkens, P 2012, ' Digital canvas removal in paintings ', Signal Processing , vol. 92, pp. 1166-1171. < http://www.sciencedirect.com/science/article/pii/S0165168411003975 >
Cornelis, B. , Dooms, A. , Cornelis, J. , & Schelkens, P. (2012). Digital canvas removal in paintings . Signal Processing , 92 , 1166-1171. http://www.sciencedirect.com/science/article/pii/S0165168411003975
@article{5a2fde36644547898f7c7fe6cac6745c,
title = " Digital canvas removal in paintings " ,
abstract = " The periodic structure of the underlying support of paintings on canvas can become quite prominent and disturbing in high resolution digital recordings. In this paper, we construct a new model and method for the digital removal of canvas which is considered as a noise component superimposed on the painting artwork. The high resolution of the images prohibits the efficient application of existing adaptive denoising filters. Hence, a two-step approach is proposed. First a (smoothing) Wiener filter is applied to the complete image. The second step consists of a spatially adaptive extension with low-complexity to obtain a generic digital canvas removal filter. " ,
keywords = " Digital painting analysis, Canvas removal, Denoising, Periodic noise, Wiener filter " ,
author = " Bruno Cornelis and Ann Dooms and Jan Cornelis and Peter Schelkens " ,
year = " 2012 " ,
month = apr,
language = " English " ,
volume = " 92 " ,
pages = " 11661171 " ,
journal = " Signal Processing " ,
issn = " 0165-1684 " ,
publisher = " Elsevier " ,
}