Skip to main content

Integration of Digital Image Matching and Multi Image Shape from Shading

  • Conference paper
Mustererkennung 1992

Part of the book series: Informatik aktuell ((INFORMAT))

Abstract

Classical shape from shading (SFS) is based on the analysis of the intensity values of a single digital image in order to derive three dimensional information of the depicted scene. It involves the orthographic projection for the transformation from object to image space and has been successfully applied to weakly textured images. In general the illumination conditions must be known, Lambertian reflection and constant albedo must be assumed for the object surface, and only surface slopes can be determined. Digital image matching on the other hand needs at least two images of the same scene, which must be well textured. Therefore, the two methods are complementary to each other, and a combined model should yield better results than any of the two separate ones.

In this paper a new global approach is presented integrating digital image matching and multi image SFS in object space. In a least squares adjustment the unknowns (geometric and radiometric parameters of the object surface) are estimated from the pixel intensity values and control information. The perspective projection is used for the transformation from object to image space.

The approach is investigated using synthetic images. The main results of this study are the following:

  • Heights of a digital terrain model (DTM) or a digital surface model (DSM) instead of surface slopes can be calculated directly using multi image SFS alone or the combined approach (in this paper the term “DTM” stands for both, DTM and DSM).

  • There is no need for conjugate points in the multi image SFS approach. This is especially important, since in weakly textured images the correspondence problem is extremely hard to solve due to the lack of large image intensity gradients.

  • If variable albedo is present in parts of the object surface only the combined approach yields correct results. Multi image SFS and digital image matching alone fail in this case.

Updated version of a paper published in the International Archives of Photogrammetry and Remote Sensing, Vol (29), Part 3, 1992.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Ackermann F., Hahn M., 1991: Image pyramids for digital photogrammetry, in: Ebner H., Fritsch D., Heipke C. (Eds.), Digital Photogrammetrie Systems, Wichmann, Karlsruhe, 43–58.

    Google Scholar 

  • Barnard S.T., Fischler M.A., 1982: Computational stereo, Association for Computing Machinery Computing Surveys (14) 4, 553–571.

    Article  Google Scholar 

  • Barnard S.T., Thompson W.B., 1980: Disparity analysis of images, IEEE-PAMI (2) 4, 333–340.

    Article  Google Scholar 

  • Boyer K.L., Kak A.C., 1988: Structural stereopsis for 3-D vision, IEEE-PAMI (10) 2, 144–166.

    Article  Google Scholar 

  • Davis P.A., Sonderblom L.A., 1984: Modelling crater topography and albedo from monoscopic Viking orbiter images, Journal of Geophysical Research (89), 9449–9457.

    Article  Google Scholar 

  • Ebner H., Fritsch D., Gillessen W., Heipke C., 1987: Integration von Bildzuordnung und Objektrekonstruktion innerhalb der digitalen Photogrammetrie, BuL (55) 5, 194–203.

    Google Scholar 

  • Ebner H., Heipke C., 1988: Integration of digital image matching and object surface reconstruction, IntArchPhRS (27) B11, III-534–545.

    Google Scholar 

  • Ehlers M., 1983: Untersuchungen von digitalen Korrelationsverfahren zur Entzerrung von Fernerkundungsaufnahmen, Wissenschaftliche Arbeiten der Fachrichtung Vermessung der Universität Hannover 121.

    Google Scholar 

  • Förstner W., 1982: On the geometric precision of digital correlation, IntArchPhRS (24) 3, 176–189.

    Google Scholar 

  • Förstner W., 1986: A feature based correspondence algorithm for image matching, IntArchPhRS (26) 3/3, 150–166.

    Google Scholar 

  • de Graaf A.J., Korsten M.J., Houkes Z., 1990: Estimation of position and orientation of objects from stereo images, in: Großkopf R. (Ed.), Mustererkennung 1990, Proceedings, 12. DAGM-Symposium Aalen, Springer, Berlin, 348–355.

    Google Scholar 

  • Grimson W.E.L., 1984: Binocular shading and visual surface reconstruction, CVGIP (28) 1, 19–43.

    Google Scholar 

  • Grün A., 1985: Adaptive least squares correlation: a powerful image matching technique, South African Journal of Photogrammetry, Remote Sensing and Cartography (14) 3, 175–187.

    Google Scholar 

  • Hannah M.J., 1989: A system for digital stereo image matching, PE&RS (55) 12, 1765–1770.

    Google Scholar 

  • Heipke C., 1990: Integration von digitaler Bildzuordnung, Punktbestimmung, Oberflächenrekonstruktion und Orthoprojektion in der digitalen Photogrammetrie, DGK, Reihe C, 366.

    Google Scholar 

  • Heipke C., 1991: A global approach for least squares image matching and surface reconstruction in object space, ACSM-ASPRS Auto Carto 10 Annual Convention, Technical Papers (5), 161–171; also in press, PE&RS (58).

    Google Scholar 

  • Helava U.V., 1988: Object-space least-squares correlation, PE&RS (54) 6, 711–714.

    Google Scholar 

  • Horn B.K.P., 1970: Shape from shading: a method for obtaining the shape of a smooth opaque object from one view, Ph. D. thesis, Department of Electrical Engineering, MIT.

    Google Scholar 

  • Horn B.K.P., 1986: Robot Vision, The MIT Press, Cambridge.

    Google Scholar 

  • Horn B.K.P., 1990: Height and gradient from shading, IJCV (5) 1, 37–75.

    Article  Google Scholar 

  • Horn B.K.P., Brooks M.J., 1986: The variational approach to shape from shading, CVGIP (33) 2, 174–208.

    Google Scholar 

  • Horn B.K.P., Brooks M.J. (Eds.), 1989: Shape from shading, The MIT Press, Cambridge.

    Google Scholar 

  • Ikeuchi K., Horn B.K.P., 1981: Numerical shape from shading and occluding boundaries, Artificial Intelligence (17) 1-3, 141–184.

    Article  Google Scholar 

  • Julesz B., 1971: Foundation of cyclopean perception, University of Chicago Press, Chicago.

    Google Scholar 

  • Kim B., Burger P., 1991: Depth and shape from shading using the photometric stereo method, CVGIP — Image Understanding (54)3, 416–427.

    Article  MATH  Google Scholar 

  • Kraus K., 1982: Photogrammetrie Band 1 — Grundlagen und Standardverfahrem, Dümmler, Bonn.

    Google Scholar 

  • Kraus K., Schneider W., 1988: Fernerkundung Band 1 — Physikalische Grundlagen und Aufnahmetechniken, Dümmler, Bonn.

    Google Scholar 

  • Leclerc Y.G., Bobick A.F., 1991: The direct computation of height from shading, Proceedings, IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 552–558.

    Google Scholar 

  • Lee S., Brady M., 1991: Integrating stereo and photometric stereo to monitor the development of glaucoma, Image and Vision Computing (9) 1, 39–44.

    Article  Google Scholar 

  • Mallot H., 1991: Frühe Bildverarbeitung in neuronaler Architektur, in: Radig B. (Ed.), Mustererkennung 1991, Proceedings, 13. DAGM-Symposium München, Springer, Berlin, 19–34.

    Google Scholar 

  • Marr D., 1982: Vision, Freeman, New York.

    Google Scholar 

  • Marr D., Poggio T., 1979: A computational theory of human stereo vision, Proceedings of the Royal Society London B. 204, 301–328.

    Article  Google Scholar 

  • McKeown D.M., 1991: Information fusion in cartographic feature extraction, in: Ebner H., Fritsch D., Heipke C. (Eds.), Digital Photogrammetric Systems, Wichmann, Karlsruhe, 103–110.

    Google Scholar 

  • Rindfleisch T., 1966: Photometric method for lunar topography, Photogrammetric Engineering (32) 2, 262–277.

    Google Scholar 

  • Rosenholm D., 1986: Accuracy improvement of digital matching for evaluation of digital terrain models, IntArchPhRS (26) 3/2, 573–587.

    Google Scholar 

  • Shapiro L.G., Haralick R.M., 1987: Relational matching, Applied Optics (26) 10, 1845–1851.

    Article  Google Scholar 

  • Shao M., Chellappa R., Simchony T., 1991: Reconstructing a 3-D depth map from one or more images, CVGIP — Image Understanding (53) 2, 219–226.

    Article  MATH  Google Scholar 

  • Sharp J. V., Christensen R.L., Gilman W.L., Schulman F.D., 1965: Automatic map compilation using digital techniques, PE&RS (31) 3, 223–239.

    Google Scholar 

  • Strat T.M., 1979: A numerical method for shape from shading from single images, S.M. thesis, Department of Electrical Engineering and Computer Science, MIT.

    Google Scholar 

  • Szelinski R., 1991: Fast shape from shading, CVGIP — Image Understanding (53) 2, 129–153.

    Article  Google Scholar 

  • Thomas J., Kober W., Leberl F., 1991: Multiple image SAR shape from shading, PE&RS (57) 1, 51–59.

    Google Scholar 

  • Woodham R J., 1980: Photometric method for determining surface orientation from multiple images, Optical Engineering (19) 1, 139–144.

    Google Scholar 

  • Wrobel B., 1987: Digitale Bildzuordnung durch Facetten mit Hilfe von Objektraummodellen, BuL (55) 3, 93–101.

    Google Scholar 

  • Wrobel B., 1989: Geometrisch-physikalische Grundlagen der digitalen Bildmessung, Schriftenreihe Institut für Photogrammetrie, Universität Stuttgart (13), 223–242.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1992 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Heipke, C. (1992). Integration of Digital Image Matching and Multi Image Shape from Shading. In: Fuchs, S., Hoffmann, R. (eds) Mustererkennung 1992. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77785-1_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-77785-1_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55936-8

  • Online ISBN: 978-3-642-77785-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics