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High dynamic range in infrared image using super-framing framework
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Paper Abstract

High dynamic range (HDR) imaging is an area of increasing importance, but most display devices still have limited dynamic range(LDR). Dynamic range represents the ability of the imaging system to restore the real scene. With the continuous development of imaging systems toward high sensitivity, a higher dynamic range imaging system is more and more demanded. Aiming at the dynamic range expansion problem of the cooled infrared imaging system, this paper proposed a super-framing algorithm to enlarge image dynamic range. Specifically, a model for automatically selecting the integration settings of such images is presented based on the camera characteristic function. It is used to calculate the optimal integration time of different temperature targets in the scene. Afterwards, fuse these frames into an image which possesses all well-exposed areas and give a sense of capturing a high dynamic range scene. Experimental results demonstrate that the system dynamic range can effectively improve 10dB when fusing three frame images. the system dynamic range is from 70dB up to 80dB, the temperature range is from 20°C up to 370°C. The strength of the proposed method lies in its ability to avoid high computational cost using traditional irradiance method applied in the infrared imaging field. Its great performance is conductive to human observation with good imaging effect, low computational complexity and engineering feasibility. The method can be applied to engine test, explosion flame and other high dynamic scenes with high temperature targets.

Paper Details

Date Published: 18 December 2019
PDF: 9 pages
Proc. SPIE 11338, AOPC 2019: Optical Sensing and Imaging Technology, 113381Q (18 December 2019); doi: 10.1117/12.2544485
Show Author Affiliations
Wenjia Li, Tianjin Jinhang Institute of Technical Physics (China)
Ke Li, Tianjin Jinhang Institute of Technical Physics (China)
Zhiheng Zhang, Tianjin Jinhang Institute of Technical Physics (China)


Published in SPIE Proceedings Vol. 11338:
AOPC 2019: Optical Sensing and Imaging Technology
John E. Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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