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Proceedings Paper

Adaptive automatic terrain extraction
Author(s): Bingcai Zhang; Scott Miller
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Paper Abstract

Automatic terrain extraction (ATE) is a key component of digital photogrammetric software. Image correlation has been widely used in ATE and has been proved to be a reliable and accurate algorithm. A successful implementation of image correlation largely depends on a set of correct parameters which control the algorithm. The set of parameters should change adaptively according to several characteristics including terrain type, signal power, flying height, X and Y parallax, and image noise level. This paper discusses a new adaptive automatic terrain extraction (AATE) system which uses an inference engine to generate the set of image correlation parameters. In addition to an inference engine, AATE can exploit multiple images and multiple bands, and it contains improved methods for correcting image noise and Y parallax errors. The overall result is a more user friendly and productive system which generates substantially more accurate digital elevation data when compared to the previous non- adaptive ATE. Owing to its adaptivity, AATE works well on large and small scale images. This paper presents the theoretical foundation of AATE and the issues arising in the practical implementation. This paper also presents some comparison results between non-adaptive ATE and AATE for various terrain types and flying heights.

Paper Details

Date Published: 5 August 1997
PDF: 10 pages
Proc. SPIE 3072, Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III, (5 August 1997); doi: 10.1117/12.281065
Show Author Affiliations
Bingcai Zhang, Helava Associates Inc. (United States)
Scott Miller, Helava Associates Inc. (United States)

Published in SPIE Proceedings Vol. 3072:
Integrating Photogrammetric Techniques with Scene Analysis and Machine Vision III
David M. McKeown Jr.; J. Chris McGlone; Olivier Jamet, Editor(s)

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