Restoration of ancient documents using sparse image representation

Archival, ancient manuscripts constitute a primary carrier of information about our history and civilisation process. In the recent past they have been the object of intensive digitisation campaigns, aimed at their preservation, accessibility and analysis. At ISTI-CNR, the availability of the diverse information contained in the multispectral, multisensory and multiview digital acquisitions of these documents has been exploited to develop several dedicated image processing algorithms. The aim of these algorithms is to enhance the quality and reveal the obscured contents of the manuscripts, while preserving their best original appearance according to the concept of "virtual restoration". Following this research line, within an ERCIM "Alain Bensoussan" Fellowship, we are now studying sparse image representation and dictionary learning methods to restore the natural appearance of ancient manuscripts affected by spurious patterns due to various ageing degradations.