Presentation + Paper
1 May 2017 Enhancement of thermal imagery using a low-cost high-resolution visual spectrum camera for scene understanding
Ryan E. Smith, Derek T. Anderson, Cindy L. Bethel, Chris Archibald
Author Affiliations +
Abstract
Thermal-infrared cameras are used for signal/image processing and computer vision in numerous military and civilian applications. However, the cost of high quality (e.g., low noise, accurate temperature measurement, etc.) and high resolution thermal sensors is often a limiting factor. On the other hand, high resolution visual spectrum cameras are readily available and typically inexpensive. Herein, we outline a way to upsample thermal imagery with respect to a high resolution visual spectrum camera using Markov random field theory. This paper also explores the tradeoffs and impact of upsampling, both qualitatively and quantitatively. Our preliminary results demonstrate the successful use of this approach for human detection and accurate propagation of thermal measurements in an image for more general tasks like scene understanding. A tradeoff analysis of the cost-to-performance as the resolution of the thermal camera decreases is provided.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ryan E. Smith, Derek T. Anderson, Cindy L. Bethel, and Chris Archibald "Enhancement of thermal imagery using a low-cost high-resolution visual spectrum camera for scene understanding", Proc. SPIE 10202, Automatic Target Recognition XXVII, 102020D (1 May 2017); https://doi.org/10.1117/12.2262380
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KEYWORDS
Cameras

Magnetorheological finishing

Image resolution

RGB color model

Thermography

Sensors

Image processing

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