High dynamic range in infrared image using super-framing framework

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.

[1]  Sang Ho Kim,et al.  Fusion of high dynamic range scene photos , 2009, Electronic Imaging.

[2]  Manish Narwaria,et al.  Tone mapping-based high-dynamic-range image compression: study of optimization criterion and perceptual quality , 2013 .

[3]  Shree K. Nayar,et al.  Radiometric self calibration , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[4]  Yao Li-bin Low-light-level CMOS Image Sensor Technique , 2013 .

[5]  R. Ramirez Orozco,et al.  Full high-dynamic range images for dynamic scenes , 2012, Photonics Europe.

[6]  Jitendra Malik,et al.  Image-based modeling and rendering of architecture with interactive photogrammetry and view-dependent texture mapping , 1998, ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187).