Paper
22 March 1996 Suitability of wavelet image data compression for the derivation of digital elevation models
Michael Thierschmann, Peter Reinartz, Manfred Lehner
Author Affiliations +
Abstract
Digital elevation models will be more and more important concerning the generation of geo information systems. Unfortunately, the consumption of image data is very high. To reduce data transfer time and cost high efficient image data compression techniques are required. LuRaTech is under way developing a wavelet based image data compression software for space applications uses, primarily. The question to be answered is how the individual processing steps of digital elevation modeling are influenced by the quality of image data sources. Very important in this scope is the automatic image matching and photogrammetric adjustment process. In this paper we discuss the automatic impact of losses due to data compression on the photogrammetric evaluation of 3-line scanner imagery coming from the modular optoelectronic multispectral scanner (MOMS-02), which has been flown successfully on the German space shuttle mission D2 in April/May 1993. We look at two methods for the quantification of the impact on parallax measurements. The results focus on the comparison of the automatically extracted interest-operator points, the displacement of objects for different compression levels, comparison of mean values of the quality figure, comparison of correlation value, standard deviation of object displacements, number of conjugate points, mean of maximum of correlation coefficient and the histogram statistics of different images for various compression levels.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael Thierschmann, Peter Reinartz, and Manfred Lehner "Suitability of wavelet image data compression for the derivation of digital elevation models", Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); https://doi.org/10.1117/12.236030
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Cited by 1 scholarly publication.
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KEYWORDS
Image compression

Image processing

Scanners

Data modeling

Image quality

Wavelets

Data compression

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