Improving infrared images for Standoff object detection

被引：2

作者：

Hanton K. ^{[1
]}

Butavicius M. ^{[2
]}

Johnson R. ^{[3
]}

Sunde J. ^{[3
]}

机构：

[1] School of Electrical and Information Engineering, University of South Australia, Mawson Lakes, Adelaide

[2] Command, Control, Communications and Intelligence Division, Defence Science and Technology Organisation, PO Box 1500, Edinburgh, 5111, SA

[3] Weapons System Division, Defence Science and Technology Organisation, PO Box 1500, Edinburgh, 5111, SA

来源：

Journal of Computing and Information Technology | 2010年 / 18卷 / 02期

关键词：

Infrared imaging; Performance improvement measure; Standoff detection; Superresolution;

D O I：

10.2498/cit.1001817

中图分类号：

学科分类号：

摘要：

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 number and size of pixels in the imaging sensor can also contribute to image degradation through under-sampling of the image. Establishing processes that enhance degraded or under-sampled infrared images so that objects of interest can be recognised with more certainty is important. Super-resolution image reconstruction and deconvolution methods are explored, as well as performance improvement measures.

引用

页码：151 / 157

页数：6

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