Xiunguang Zhou
The shaded-relief image was created using the Lambert photometric function (X. Zhou and E. Dorrer, 1995).
Considering that the albedo is assumed constant in the shaded-relief image and the limitation of the Lambert model, the
two images are quite similar. It is an overcritical method to verify the quality of the DEM by comparing its shaded-
relief with its original image.
There are some errant points in the DEM (in the right area of the DEM), which can be seen in the shaded-relief image.
The errors come from unmatched points. Errors such as these can be easily removed if an interpolation is used in the
DEM generation like the usual way. An interpolation was not performed in this case to show the high accuracy and
detail possible using this technique.
REFERNENCES
Ackermann F., Hahn M., 1991. Image pyra-mids for digital photogrammetry. Digital Photogrammetric Systems,
Wichmann, Karlsruhe, pp. 43-58
Barnea D., Silverman H., 1972. A class of algorithms for fast digital image registration. IEEE Trans. on Computers,
Vol. C-21, No. 2, pp. 178-186
Cucka P., Rosenfeld A., 1992. Linear feature compatibility for Pattern-matching relaxation. Pattern Recognition,
Vol. 25, No.2, pp. 189—196
Fórstner W., 1982. On the Geometric precision of digital correlation. Inter. Arc. Photo. Remote Sensing, 24(3), pp.
176-189
Fórstner W., 1986. A feature based correspondence algorithm for image matching. Int. Arc. Phot. Remote Sensing,
26(3), pp. 1 - 17
Grün A., 1985. Adaptive least squares correlation: a powerful image matching technique. S. Afr. J. of Phot., Remote
Sensing and Cartography Cartography, 14 (3), pp. 175-187
Hannah M., 1989. A system for digital stereo image matching. Phot. Eng. and Remote Sensing, 55(12), pp. 1765-1770
Lemons M., 1988. A survey on stereo matching techniques. Int. Arc. Phot. Remote Sensing, Vol. 27, Part B 8, pp. v 11 -
23
Murtagh F., 1992. A feature-based o (x : ) approach to point matching. Inter. Con. on Pattern Recognition, B, pp. 174-
177
Otto G., Chau T., 1989. “Region-growing" algorithm for matching of terrain images. Image and vision Computing,
Vol. 7, No. 2, pp. 83-94
Papanikolaou K., Derenyi E., 1988. Structural matching of digital images and terrain models. ISPRS, Part B27 (3), pp.
669-678
Rosenholm D., 1986. Accuracy improvement of digital matching for evaluation of digital terrain models. Int. Arc. Phot.
Remote Sensing, 26(3), pp. 573- 587
Shapiro L., Haralick R., 1987. Relational matching. Applied Optics, Vol. 26, pp. 1845-1851
Zhou X., Dorrer E., 1994. A non-error reconstruction of multiresolution discrete wavelet representation and its fast
algorithm. SPIE vol. 2242, Wavelet Applications, pp236--247
Zhou X., Dorrer E., 1994. An Automatic Image Matching Algorithm Based on Wavelet Decomposition. Proceedings of
ISPRS, Commission III, on "Spatial Information from Digital Photogrammetry and Computer Vision", pp.951—960
Zhou X., Dorrer E., 1995. An Adaptive Algorithm of Shaded-relief Images from DEMs Based on Wavelet Transform",
Proceedings of ISPRS & SPIE, on "Digital Photogrammetry and Remote Sensing '95", SPIE vol.2646, pp.212—224
Zhou X., Dorrer E., 1996. De-shading: Integrated Approach to Photometric Model, Surface Shape and Reflectance
Properties. Proceedings of ISPRS Congress, Vol XXXI, B3, WG II/2, PP.1028—1035
Zhou X., Dorrer E., 1997. A New Edge Detection Algorithm Based on Wavelet Transform. Proceedings of Second
Turkish-German Joint Geodetic Days, PP. 727—736
Zong J., Li J., Schenk T., 1992. Aerial image matching based on zero-crossing. Int. Arc. Phot. Remote Sensing,
Commission III, pp. 144- 150
1062 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B3. Amsterdam 2000.
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