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DIRSIG 5: core design and implementation
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Paper Abstract

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model has been developed at the Rochester Institute of Technology (RIT) for over two decades. The last major update of the model, DIRSIG 4, built on an established, first-principles, multi- and hyper-spectral scene simulation tool. It introduced a modern and flexible software architecture to support new sensor modalities and more complex and dynamic scenes. Since that time, the needs of the user community have grown and diversified in tandem with the computational capabilities of modern hardware. Faced with a desire to model more complex, multi-component systems that are beyond the original intent and capabilities of an aging software design, a new version of DIRSIG, version 5, is being introduced to the community. This paper describes the core of DIRSIG 5 that is responsible for linking the disparate sensor, scene, and environmental models together, spatially, temporally, and parametrically. The spatial relationships are governed by a planet-centric universe model encompassing a whole globe digital elevation and optical property model, the scene model(s), globally varying atmospheric models, and a space model. Temporal relationships are driven by a formal modeling and simulation architecture based on approaches used in engineering and biological sciences to model highly dynamic and interactive systems. Finally, the parametric interfaces are described by a universal data model that facilitates scripting, inter-dependent properties and user interface construction. The design of these components will be presented along with specific module implementation details. These simulation tools will be used to demonstrate some of the new capabilities and applications of DIRSIG 5.

Paper Details

Date Published: 9 May 2012
PDF: 9 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900H (9 May 2012); doi: 10.1117/12.919321
Show Author Affiliations
Adam A. Goodenough, Rochester Institute of Technology (United States)
Scott D. Brown, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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