RSS-Feed abonnieren
DOI: 10.1055/s-2005-872817
Georg Thieme Verlag Stuttgart KG · New York
Volume Interpolation of CT Images from Tree Trunks
Publikationsverlauf
Received: April 28, 2005
Accepted: July 15, 2005
Publikationsdatum:
02. Januar 2006 (online)
Abstract
Computerized tomography as a non-destructive scanning method to analyze wood structures has become an important technique in tree research. The possibility to reconstruct three-dimensional volumes based on a number of slices of two-dimensional data from CT scans is strongly dependent on the number of measured slices. Radial basis function methods can be successfully used to interpolate CT images with the aim of obtaining a satisfactory reconstruction of tree trunks. In contrast to standard interpolation techniques, our method takes into account that wood structures differ more in the radial than in the longitudinal direction. Therefore we obtain better interpolation results for wood structures.
Key words
Radial basis function interpolation - kriging methods - minimal-norm interpolation - three-dimensional reconstruction - computerized tomography - analysis of wood structures - wood density - year ring analysis.
References
- 1 Araman P. A., Schmoldt D. L., Cho T., Zhu D., Conners R. W., Kline D. E.. Machine vision systems for processing hardwood lumber and logs. AI Applications. (1992); 6 13-26
- 2 Beatson R. K., Light W. A., Billings S.. Fast solution of the radial basis function interpolation equations: domain decomposition methods. SIAM Journal on Scientific Computing. (2000); 22 1717-1740
- 3 Bhandarkar S. M., Faust T. D., Tang M.. CATALOG: a system for detection and rendering of internal log defects using computer tomography. Machine Vision and Applications. (1999); 11 171-190
- 4 Buhmann M. D.. Radial Basis Functions: Theory and Implementations. Cambridge Monographs on Applied and Computational Mathematics 12. Cambridge; Cambridge University Press (2003)
- 5 Courtois H.. Einfluss von Rohdichte, Holzfeuchtigkeit und Jahrringbreite auf den Abbau des Nadelholzes durch Fomes annosus (FR.) CKE. Holz als Roh- und Werkstoff. (1970); 28 67-75
-
6 Duchon J..
Splines minimizing rotation-invariant semi-norms in Sobolev spaces. Schempp, W., and Zeller, K., eds. Constructive Theory of Functions of Several Variables, Lecture Notes in Mathmatics 571. New York; Springer (1976): 85-100 - 7 Fromm J. H., Sautter I., Matthies D., Kremer J., Schumacher P., Ganter C.. Xylem water content and wood density in spruce and oak trees detected by high-resolution computed tomography. Plant Physiology. (2001); 127 416-425
- 8 Habermehl A.. A new non-destructive method for determining internal wood condition and decay in living trees. Part I: method and apparatus. Arboricultural Journal, Academic Publishers,. (1982); 6 1-8
- 9 Herms D. A., Mattson W. J.. The dilemma of plants: to grow or defend. The Quarterly Review of Biology. (1992); 67 283-335
- 10 Kak A. C., Slaney M.. Principles of Computerized Tomographic Imaging. SIAM Classics in Applied Mathematics 33. Philadelphia; Society for Industrial and Applied Mathematics (2001)
- 11 Lindgren O.. Medical CAT‐scanning: X‐ray absorption coefficients, CT‐numbers and their relation to wood density. Wood Science and Technology. (1991); 25 341-349
- 12 Matheron G.. Les Variables Régionalisées et leur Estimation. Paris; Masson (1965)
- 13 Matheron G.. The intrinsic random functions and their applications. Advances in Applied Probability. (1973); 5 439-468
- 14 Mattheck C., Kubler H.. Wood - The Internal Optimization of Trees. Berlin; Springer (1998): 130
- 15 Matyssek R., Schnyder H., Elstner E.-F., Munch J.-C., Pretzsch H., Sandermann H.. Growth and parasite defence in plants; the balance between resource sequestration and retention: in lieu of a guest editorial. Plant Biology. (2002); 4 133-136
- 16 Oja J., Temnerud E.. The appearance of resin pockets in CT‐images of Norway spruce (Picea abies [L.] Karst.). Holz als Roh- und Werkstoff. (1999); 57 400-406
- 17 Parziale G., Rinnhofer A.. Resin pocket enhancement through anisotropic diffusion. Proceedings of 5th International Conference on Image Processing and Scanning Wood, Graz. (2003): 161-169
- 18 Peltola H., Kellomäki S., Väisänen H., Ikonen V.-P.. A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce, and birch. Canadian Journal of Forest Research. (1999); 29 647-661
- 19 Roderick M., Berry L.. Linking wood density with tree growth and environment: a theoretical analysis based on the motion of water. New Phytologist. (2001); 149 473-485
- 21 Sepulveda P.. Measurement of spiral grain with computed tomography. Journal of Wood Science. (2001); 47 289-293
- 20 Shain L., Hillis W. E.. Phenolic extractives in Norway spruce and their effects on Fomes annosus. Phytopathology. (1971); 61 841-845
- 22 Temnerud E.. The occurrences of resin pockets in sawlog populations of Picea abies (L.) Karst. from five geographic regions in Sweden. Scandinavian Journal of Forest Research. (1999); 14 143-155
- 23 Wernsdörfer H., Reck P., Seeling U., Becker G., Seifert T.. Erkennung und Messung des Reaktionsholzes bei Fichte (Picea abies [L.] Karst.) mittels Verfahren der digitalen Bildanalyse. Holz als Roh- und Werkstoff. (2004); 62 243-252
- 24 Wipfler P., Seifert T., Heerdt C., Werner H., Pretzsch H.. Growth of adult Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.) under free-air ozone fumigation. Plant Biology. (2005); DOI: 10.1055/s-2005-872871
W. zu Castell
Institute of Biomathematics and Biometry
GSF - National Research Center for Environment and Health
Ingolstädter Landstraße 1
85764 Neuherberg
Germany
eMail: castell@gsf.de
Guest Editor: R. Matyssek