Infrared Image Enhancement using $H_{infty}$ Bounds for Surveillance Applications

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Infrared Image Enhancement using $H_{infty}$ Bounds for Surveillance Applications

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dc.contributor.author Qidwai, Uvais
dc.date.accessioned 2009-12-29T05:41:33Z
dc.date.available 2009-12-29T05:41:33Z
dc.date.issued 2008-06-24
dc.identifier.citation Volume 17, Issue 8, Aug. 2008 Page(s):1274 - 1282 en_US
dc.identifier.uri http://dx.doi.org/10.1109/TIP.2008.925377
dc.identifier.uri http://hdl.handle.net/10576/10541
dc.description.abstract In this paper, two algorithms have been presented to enhance the infrared (IR) images. Using the autoregressive moving average model structure and Hinfin optimal bounds, the image pixels are mapped from the IR pixel space into normal optical image space, thus enhancing the IR image for improved visual quality. Although Hinfin-based system identification algorithms are very common now, they are not quite suitable for real-time applications owing to their complexity. However, many variants of such algorithms are possible that can overcome this constraint. Two such algorithms have been developed and implemented in this paper. Theoretical and algorithmic results show remarkable enhancement in the acquired images. This will help in enhancing the visual quality of IR images for surveillance applications. en_US
dc.language.iso en en_US
dc.subject image enhancement en_US
dc.subject image modeling en_US
dc.subject infrared (IR) image en_US
dc.subject processing en_US
dc.title Infrared Image Enhancement using $H_{infty}$ Bounds for Surveillance Applications en_US
dc.type Article en_US

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