DIRSIG5: Next-Generation Remote Sensing Data and Image Simulation Framework
| Autor: | Scott D. Brown, Adam A. Goodenough |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Atmospheric Science
digital imaging and remote sensing image generation (DIRSIG) 010504 meteorology & atmospheric sciences Computer science Computation Geophysics. Cosmic physics sensors User requirements document 01 natural sciences Data modeling 010309 optics Computer graphics modeling and simulation scene simulation 0103 physical sciences Computers in Earth Sciences Representation (mathematics) TC1501-1800 0105 earth and related environmental sciences Remote sensing QC801-809 Digital imaging Ocean engineering Remote sensing (archaeology) Multithreading simulations |
| Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 10, Iss 11, Pp 4818-4833 (2017) |
| ISSN: | 2151-1535 1939-1404 |
| DOI: | 10.1109/jstars.2017.2758964 |
| Popis: | The digital imaging and remote sensing image generation model is a physics-based image and data simulation model that is primarily used to generate synthetic imagery across the visible to thermal infrared regions using engineering-driven descriptions of remote sensing systems. The model recently went through a major redesign and reimplementation effort to address changes in user requirements and numerical computation trends that have emerged in the 15 years since the last major development effort. The new model architecture adopts some of the latest light transport algorithms matured by the computer graphics community and features a framework that is easily parallelized at the microscale (multithreading) and macroscale (cluster-based computing). A detailed description of the framework is provided, including a novel method for efficiently storing, evaluating, integrating, and sampling spherical and hemispherical datasets appropriate for the representation of modeled or measured bidirectional scattering, reflectance, and transmission distribution functions. The capabilities of the model are then briefly demonstrated and cross-verified with scenarios of interest to the remote sensing community. |
| Databáze: | OpenAIRE |
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