Historical document image restoration using multispectral imaging system

Thousands of valuable historical documents stored on the shelves of national libraries throughout the world are waiting to be scanned in order to facilitate access to the information they contain. The first major problem faced is degradation, which renders the visual quality of the document very poor, and in most cases, difficult to decipher. This work is part of our collaboration with the BAnQ (Bibliothèque et Archive Nationales de Québec), which aims to propose a new approach to provide the end user (historian, scholars, researchers, etc.) with an acceptable visualization of these images. To that end, we have adopted a multispectral imaging system capable of producing images in invisible lighting, such as infrared lights. In fact, in addition to visible (color) images, the additional information provided by the infrared spectrum as well as the physical properties of the ink (used on these historical documents) will be further incorporated into a mathematical model, transforming the degraded image into its new clean version suitable for visualization. Depending on the degree of degradation, the problem of cleaning them could be resolved by image enhancement and restoration, whereby the degradation could be isolated in the Infrared spectrum, and then eliminated in the visible spectrum. The final color image is then reconstructed from the enhanced visible spectra (red, green and blue). The first experimental results are promising and our aim in collaboration with the BAnQ, is to give this documentary heritage to the public and build an intelligent engine for accessing the documents.

► A new algorithm for historical document image restoration is introduced. ► The algorithm aims to restore the historical document images from degradation. ► The color document image is then reconstructed with preservation of the texture. ► Degradations are isolated in one of the IR bands and inpainted in the color bands. ► Evaluation is performed to show the effectiveness of the proposed algorithm.