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Proceedings Paper

Preparing Data Bases For Perspective Scene Generation
Author(s): Arliss E. Whiteside
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Paper Abstract

Preparing data bases for highly-realistic perspective scene generation has several difficult aspects, including mosaicking images and representing vertical features. A perspective scene is a digital image generated to simulate viewing the ground from a selected observation point, looking in a selected direction. Each perspective scene is generated from a data base containing digital image data and grid elevation data. In many cases, several digital images must be combined or mosaicked to produce the image data needed for generation of one or more perspective scenes. The image mosaicking requirements to prepare data bases for perspective scene generation are described. Alternative mosaicking approaches are then reviewed, identifying the more attractive methods. A semi-automatic mosaicking process using these methods is outlined. Digital images have been successfully mosaicked using this process, and experimental results are shown. The digital image data is normally vertical or orthorectified, and thus cannot directly represent the appearance of vertical and overhanging sides of ground features. The requirements are described for representing the sides of features to adequately support realistic perspective scene generation. Alternative feature representation approaches are then reviewed, selecting the more attractive methods. Planar feature surfaces can be extracted, including the surface location in ground coordinates and image data showing the appearance of the surface. A feature data format and corresponding perspective scene generation algorithms are outlined, and experimental results are shown.

Paper Details

Date Published: 5 April 1989
PDF: 8 pages
Proc. SPIE 1075, Digital Image Processing Applications, (5 April 1989); doi: 10.1117/12.952650
Show Author Affiliations
Arliss E. Whiteside, DBA Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 1075:
Digital Image Processing Applications
Ying-Wei Lin; Ram Srinivasan, Editor(s)

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