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Interactive Visualization of Hyperspectral Images of Historical Documents
November/December 2010 (vol. 16 no. 6)
pp. 1441-1448
Seon Joo Kim, National University of Singapore
Shaojie Zhuo, National University of Singapore
Fanbo Deng, National University of Singapore
Chi-Wing Fu, Nanyang Technological University
Michael Brown, National University of Singapore
This paper presents an interactive visualization tool to study and analyze hyperspectral images (HSI) of historical documents. This work is part of a collaborative effort with the Nationaal Archief of the Netherlands (NAN) and Art Innovation, a manufacturer of hyperspectral imaging hardware designed for old and fragile documents. The NAN is actively capturing HSI of historical documents for use in a variety of tasks related to the analysis and management of archival collections, from ink and paper analysis to monitoring the effects of environmental aging. To assist their work, we have developed a comprehensive visualization tool that offers an assortment of visualization and analysis methods, including interactive spectral selection, spectral similarity analysis, time-varying data analysis and visualization, and selective spectral band fusion. This paper describes our visualization software and how it is used to facilitate the tasks needed by our collaborators. Evaluation feedback from our collaborators on how this tool benefits their work is included.

[1] ENVI.http:/
[2] PCI geomatica.http:/
[3] J. C. Anderson, L. J. Gosink, M. A. Duchaineau, and K. I. Joy, Interactive visualization of function fields by range-space segmentation. Computer Graphics Forum (Proc. of Euro Vis), 28 (3): 727–734, 2009.
[4] E. A. Bier and M. C. Stone, K. Pier, W. Buxton, and T. D. DeRose, Toolglass and magic lenses: The see-through interface. In Proc. of SIGGRAPH, pages 445–446, 1993.
[5] J. Bogaard and P. M. Whitmore, Explorations of the role of humidity fluctuations in the deterioration of paper. In Workshop of Art on Paper Books, Documents and Photographs, pages 11–15, 2002.
[6] C.-I. Chang, An information-theoretic approach to spectral variability, similarity, and discrimination for hyperspectral image analysis. IEEE Trans. on Information Theory, 46 (5): 1927–1932, 2000.
[7] M. Choi, R. Y. Kim, M.-R. Nam, and H. O. Kim, Fusion of multispectral and panchromatic satellite images using the curvelet transform. IEEE Geoscience and Remote Sensing Letters, 2 (2): 136-–140, Apr. 2005.
[8] P. Cotte and D. Dupraz, Spectral imaging of Leonardo Da Vinci's Mona Lisa: An authentic smile at 1523 dpi with additional infrared data. In IS &T Archiving Conf., pages 228–235, 2006.
[9] M. Cui, A. Razdan, J. Hu, and P. Wonka, Interactive hyperspectral image visualization using convex optimization. IEEE Trans. on Geoscience and Remote Sensing, 47 (6): 1673–1684, 2009.
[10] Q. Du and N. Raksuntorn, C. Shanshu, and R. J. Moorhead, Color display for hyperspectral imagery. IEEE Trans. on Geoscience and Remote Sensing, 46 (6): 1858–1866, 2008.
[11] R. Fattal and D. Lischinski, and M. Werman, Gradient domain high dynamic range compression. ACM Trans. on Graphics, 21 (3): 249–256, 2002.
[12] R. Gooch, Astronomers and their shady algorithms. In Proc. of IEEE Visualization Conf. 1995, pages 374–377. IEEE, Oct/No 1995.
[13] N. Jacobson and M. Gupta, Design goals and solutions for display of hyperspectral images. IEEE Trans. on Geoscience and Remote Sensing, 43 (11): 2684–2692, Nov. 2005.
[14] G. Johnson, V. Calo, and K. Gaither, Interactive visualization and analysis of transitional flow. IEEE Trans. on Visualization and Computer Graphics, 14 (6): 1420–1427, Nov.-Dec. 2008.
[15] J. Kehrer, F. Ladstadter, P. Muigg, H. Doleisch, A. Steiner, and H. Hauser, Hypothesis generation in climate research with interactive visual data exploration. IEEE Trans. on Visualization and Computer Graphics, 14 (6): 1579–1586, Nov.-Dec. 2008.
[16] M. Klein, B. J. Aalderink, R. Padoan, G. de Bruin, and T. A.G. Steemers, Quantitative hyperspectral reflectance imaging. Sensors, 8 (9): 5576–5618, 2008.
[17] D. Krishnan and R. Fergus, Dark flash photography. ACM Transanctions on Graphics (Proc. of SIGGRAPH), 28 (3): 1–11, 2009.
[18] D. Krishnan and R. Fergus, Fast image deconvolution using hyper-laplacian priors. In Proc. of Neural Information Processing Systems, pages 1033–1041, 2009.
[19] A. Kruger, C. Kubisch, G. Strauss, and B. Preim, Sinus endoscopy -application of advanced GPU volume rendering for virtual endoscopy. IEEE Trans. on Visualization and Computer Graphics, 14 (6): 1491–1498, Nov.-Dec. 2008.
[20] A. Levin, A. Zomet, S. Peleg, and Y. Weiss, Seamless image stitching in the gradient domain. In Proc. of European Conf. on Computer Vision, pages 377–389, 2004.
[21] H. Li, C.-W. Fu, and A. J. Hanson, Visualizing multiwavelength astrophysical data. IEEE Trans. on Visualization and Computer Graphics, 14 (6): 1555–1562, Nov./Dec. 2008.
[22] Z. Lu, Z. Wu, and M. S. Brown, Directed assistance for ink-bleed reduction in old documents. In IEEE Conf. on Computer Vision and Pattern Recognition, pages 88–95, 2009.
[23] G. Maino, Digitization and multispectral analysis of historical books and archival documents: Two exemplary cases. In Proc. of the International Conf. of Image Analysis and Processing, pages 119–124, 2007.
[24] J. Miller, C. W. Quammen, and M. C. Fleenor, Interactive visualization of intercluster galaxy structures in the horologium-reticulum supercluster. IEEE Trans. on Visualization and Computer Graphics, 12 (5): 1149–1156, 2006.
[25] R. Padoan, T. Steemers, M. Klein, B. Aalderink, and G. de Bruin, Quantitative hyperspectral imaging of historical documents : Technique and applications. In Proc. International Conf. on NDT of Art, pages 445–46, 2008.
[26] P. Perez, M. Gangnet, and A. Blake, Poisson image editing. ACM Trans, on Graphics (Proc. of SIGGRAPH), 22 (3): 313–318, 2003.
[27] Z. Shi and V. Govindaraju, Historical document image enhancement using background light intensity normalization. Proc. IEEE International Conf. on Pattern Recognition, pages 473–476, 2004.
[28] D. A. Socolinsky and L. B. Wolff, Multispectral image visualization through first-order fusion. IEEE Trans. on Image Processing, 11 (8): 923–931, Aug. 2002.
[29] C. L. Tan, R. Cao, and P. Shen, Restoration of archival documents using a wavelet technique. IEEE Trans. on Pattern Analysis and Machine Intelligence, 24 (10): 1399–1404, 2002.
[30] J. Zhao, Q. Pang, J. Ma, X. Zheng, and Q. Meng, Multispectral imaging system applied to element testing of biology. In Proc. of the 2008 international Conf. on Biomedical Engineering and informatics, volume 02, pages 648–651, 2008.
[31] K. Zuzak, M. Schaeberle, I. Levin, N. Lewis, J. Freeman, J. McNeil, and L. Cancio, Visible and infrared hyperspectral visualization of normal and ischemic tissue. In Proc. of the First Joint BMES/EMBS Conf., volume 2, page 1118, 1999.

Index Terms:
Hyperspectral visualization, data exploration, image fusion, document processing and analysis
Seon Joo Kim, Shaojie Zhuo, Fanbo Deng, Chi-Wing Fu, Michael Brown, "Interactive Visualization of Hyperspectral Images of Historical Documents," IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1441-1448, Nov.-Dec. 2010, doi:10.1109/TVCG.2010.172
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