Title
Using Gpu For High Fidelity Low-Cost Sensor Simulation
Keywords
Gpu; Image processing; Real-time simulation; Sensors
Abstract
Today's training system requires Forward-Looking Infra-red (FLIR), Night Vision Goggles (NVG) and special sensor effects, including gain, blur, noise, haloing, atmospherics, plumes and time of day. Traditionally, sensor simulation applications either require high performance graphics workstation or special hardware in order to have high fidelity and interactive frame-rate. Such requirements significantly raise the cost for the training system. Recent appearance of graphics processing units (GPUs) provides a new implementation method for different kinds of sensor simulation. This paper discusses framework design for sensor simulation applications leveraging the highly programmability of the GPUs' streamline. By making small changes to the High-Level Shader Language (HLSL) without change to the rendering engine, users can greatly customize their own visual effect thus providing adaptability and ease of system integration to the training system.
Publication Date
12-1-2005
Publication Title
Huntsville Simulation Conference: "Modeling and Simulation: Providing Answers to Real World Questions", HSC 2005
Number of Pages
448-453
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
84875639690 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84875639690
STARS Citation
Liao, Dezhi, "Using Gpu For High Fidelity Low-Cost Sensor Simulation" (2005). Scopus Export 2000s. 3102.
https://stars.library.ucf.edu/scopus2000/3102