Improving Infrared Images for Standoff Object Detection
The ability to detect dangerous objects (such as improvised explosive devices) from a distance is important in security and military environments. Standoff imaging can produce images that have been degraded by atmospheric turbulence, movement, blurring and other factors. The capability of an infrared (IR) camera to produce images at a safe viewing distance in a variety of conditions has been investigated, but the number and size of pixels in the imaging sensor can contribute to image degradation through under-sampling of the image [1][2]. To overcome this, Super-resolution image reconstruction and deconvolution methods are explored to enhance degraded or under-sampled IR images so that objects of interest can be recognised with more certainty. Performance improvement measures are investigated to establish whether these image processing techniques actually help a human observer detect objects of interest, and if so, in which circumstances.
References
[1] Hanton, K., Butavicius, M., Johnson, R., Sunde, J. "Improving Infrared Images for Standoff Object Detection", Proceedings of the ITI 2009, 31st International Conference on Information Technology Interfaces, June 22-25, Cavtat, Croatia. IEEE Press, 2009.
[2] Hanton, K., Butavicius, M., Sunde, J., Lozo, P. "Operator Measures
and Edge Sharpness Metrics to Assess Infrared Image Enhancement",
Proceedings of the 32nd International Convention on Information and
Communication Technology, Electronics and Microelectronics, MIPRO 2009, May
25-29, Opatija, Croatia. IEEE Press, 2009.