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CVPR
2009
IEEE

Contextual Restoration of Severely Degraded Document Images

14 years 11 months ago
Contextual Restoration of Severely Degraded Document Images
We propose an approach to restore severely degraded document images using a probabilistic context model. Un- like traditional approaches that use previously learned prior models to restore an image, we are able to learn the text model from the degraded document itself, making the approach independent of script, font, style, etc. We model the contextual relationship using an MRF. The ability to work with larger patch sizes allows us to deal with severe degradations including cuts, blobs, merges and vandalized documents. Our approach can also integrate document restoration and super-resolution into a single framework, thus directly generating high quality images from degraded documents. Experimental results show significant improve- ment in image quality on document images collected from various sources including magazines and books, and com- prehensively demonstrate the robustness and adaptability of the approach. It works well with document collections such as books, e...
Jyotirmoy Banerjee, Anoop M. Namboodiri, C. V. Jaw
Added 05 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Jyotirmoy Banerjee, Anoop M. Namboodiri, C. V. Jawahar
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