Single-frame text super-resolution: a Bayesian approach

• Published in: 2004 International Conference on Image Processing, 2004. ICIP '04 Vol. 5; pp. 3295 - 3298 Vol. 5
• Main Authors: Dalley, G., Freeman, B., Marks, J.
• Format: Conference Proceeding
• Language: English
• Published: Piscataway NJ IEEE 2004
• Subjects: Applied sciences; Artificial intelligence; Bayesian methods; Clustering algorithms; Computer science; control theory; systems; Displays; Exact sciences and technology; Gray-scale; Image resolution; Interpolation; Noise generators; Paper technology; Pattern recognition. Digital image processing. Computational geometry; Pixel; Shape; Quantization noise; Bayes estimation; High resolution; Image resolution; Image processing; Grid; Artefact; Text; Low resolution; Alignment defect; Japanese
• ISBN: 0780385543; 9780780385542
• ISSN: 1522-4880; 2381-8549
• DOI: 10.1109/ICIP.2004.1421818

We address the problem of text super-resolution: given a single image of text scanned in at low resolution from a piece of paper, return the image that is mostly likely to be generated from a noiseless high-resolution scan of the same piece of paper. In doing so, we wish to: (1) avoid introducing artifacts in the high-resolution image such as blurry edges and rounded corners, (2) recover from quantization noise and grid-alignment effects that introduce errors in the low-resolution image, and (3) handle documents with very large glyph sets such as Japanese's Kanji. Applications for this technology include improving the display of: fax documents, low-resolution scans of archival documents, and low-resolution bitmapped fonts on high-resolution output devices.