Real-time image processing for passive mmW imagery

Autor: Aaron Paolini, Daniel G. Mackrides, James Bonnett, Thomas E. Dillon, Eric J. Kelmelis, Charles Harrity, Dennis W. Prather, Christopher A. Schuetz, Richard D. Martin, Stephen Kozacik
Rok vydání: 2015
Předmět:
Zdroj: Passive and Active Millimeter-Wave Imaging XVIII.
ISSN: 0277-786X
Popis: The transmission characteristics of millimeter waves (mmWs) make them suitable for many applications in defense and security, from airport preflight scanning to penetrating degraded visual environments such as brownout or heavy fog. While the cold sky provides sufficient illumination for these images to be taken passively in outdoor scenarios, this utility comes at a cost; the diffraction limit of the longer wavelengths involved leads to lower resolution imagery compared to the visible or IR regimes, and the low power levels inherent to passive imagery allow the data to be more easily degraded by noise. Recent techniques leveraging optical upconversion have shown significant promise, but are still subject to fundamental limits in resolution and signal-to-noise ratio. To address these issues we have applied techniques developed for visible and IR imagery to decrease noise and increase resolution in mmW imagery. We have developed these techniques into fieldable software, making use of GPU platforms for real-time operation of computationally complex image processing algorithms. We present data from a passive, 77 GHz, distributed aperture, video-rate imaging platform captured during field tests at full video rate. These videos demonstrate the increase in situational awareness that can be gained through applying computational techniques in real-time without needing changes in detection hardware.
Databáze: OpenAIRE