1 May 2017 Feature-enhanced computational infrared imaging
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Abstract
Super-resolution for infrared imaging is motivated by the high cost and practical limitations of obtaining large focal plane arrays. Methods in the literature require the optical system to be modified. Here, we propose a compressive sensing based method for super-resolution using the inherent point spread function of the camera. The proposed method produces high resolution images and is robust against missing pixels. We then compare our method to other super-resolution methods in the literature and show that our method performs well for practical usage without any modification to the optical system.
Conference Presentation
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Alper Güngör, Alper Güngör, H. Emre Güven, H. Emre Güven, } "Feature-enhanced computational infrared imaging", Proc. SPIE 10222, Computational Imaging II, 1022204 (1 May 2017); doi: 10.1117/12.2262727; https://doi.org/10.1117/12.2262727
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