From Event: SPIE Commercial + Scientific Sensing and Imaging, 2017
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.
Alper Güngör and H. Emre Güven, "Feature-enhanced computational infrared imaging," Proc. SPIE 10222, Computational Imaging II, 1022204 (Presented at SPIE Commercial + Scientific Sensing and Imaging: April 09, 2017; Published: 1 May 2017); https://doi.org/10.1117/12.2262727.
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