Accurate deduction of infrared imaging features of subpixel targets based on the conversion of radiation fields of measured area targets

Ke Li; Xiao-Rui Wang; Bing-Tao Guo; Wei-Guo Zhang; Hang Yuan; Xiong-Xiong Wu; Chen Zhao

doi:10.1364/AO.57.009499

Applied Optics
Vol. 57,
Issue 31,
pp. 9499-9507
(2018)
•https://doi.org/10.1364/AO.57.009499

Accurate deduction of infrared imaging features of subpixel targets based on the conversion of radiation fields of measured area targets

Ke Li, Xiao-Rui Wang, Bing-Tao Guo, Wei-Guo Zhang, Hang Yuan, Xiong-Xiong Wu, and Chen Zhao

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Ke Li, Xiao-Rui Wang, Bing-Tao Guo, Wei-Guo Zhang, Hang Yuan, Xiong-Xiong Wu, and Chen Zhao, "Accurate deduction of infrared imaging features of subpixel targets based on the conversion of radiation fields of measured area targets," Appl. Opt. 57, 9499-9507 (2018)

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Table of Contents Category
- Imaging Systems, Image Processing, and Displays
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About this Article
History
- Original Manuscript: May 18, 2018
- Revised Manuscript: August 4, 2018
- Manuscript Accepted: September 4, 2018
- Published: October 31, 2018

Abstract

The accurate generation of infrared (IR) imaging features of subpixel targets plays a very important role in the demonstration, verification, and optimization of system design schemes as well as in research into detection algorithms for small targets in the development of remote IR early warning systems. Based on the generation mechanism of target full-link IR imaging features, this study theoretically considers target radiation characteristics, the working environment, and the spatial response and energy-conversion characteristics of IR sensors, and an accurate deduction model of IR imaging features of subpixel targets is proposed and established. First, the surface-radiation field distribution of the target and background are inverted based on the measured data and the model of radiation calibration; then, the accurate simulation of IR imaging features of subpixel targets is realized by considering the geometric transformation of the spatial imaging, the aperiodic transfer function, scale registration of spatial sampling, and radiation coupling. Finally, the accuracy of the proposed model is verified by using the outfield experiment data. The experimental results show that the IR imaging-diffusion features of subpixel targets with different duty cycles are in good agreement with the prediction results of the model. The results obtained provide data support for the demonstration, verification, and optimization of the system design scheme, as well as for research into detection algorithms of small targets in the development of remote IR early warning systems.

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Parameters	Value
Working wavelength	8–12 μm
Type of detector	MCT
Temperature ranges	$- 20 ° C - + 500 ° C$
Measurement accuracy	$\pm 1 ° C$ ( $- 20 ° C - 150 ° C$ )
	$\pm 2 ° C$ ( $150 ° C - 500 ° C$ )
Focal length	40 mm–240 mm
Field of view	$13 ° \times 10 °$
Pixel number	$320 \times 240$
Pixel pitch	$30 μm \times 30 μm$

Rectangular Target	Size
No. 1	$3.50 mm \times 3.50 mm$
No. 2	$4.95 mm \times 4.95 mm$
No. 3	$7.00 mm \times 7.00 mm$

Target	Size
Target H	$5.00 mm \times 7.00 mm$
Target E	$7.00 mm \times 10.00 mm$
Target X	$10.00 mm \times 12.00 mm$

Target		Detected Distance	Duty Cycle	Measured Pixel Number	Simulated Pixel Number
Rectangular Target	No. 1	25.00 m	93%	$3 \times 3$	$3 \times 3$
Rectangular Target	No. 2	35.00 m	97%	$3 \times 3$	$3 \times 3$
	No. 3	55.00 m	84%	$3 \times 3$	$3 \times 3$
Target H		48.00 m	67%	$3 \times 3$	$3 \times 3$
		68.00 m	34%	$3 \times 2$	$3 \times 2$
		100.00 m	15%	$2 \times 2$	$2 \times 2$
Target E		68.00 m	67%	$3 \times 3$	$3 \times 3$
		90.00 m	39%	$3 \times 2$	$3 \times 2$
		100.00 m	31%	$3 \times 2$	$3 \times 2$
Target X		85.00 m	73%	$3 \times 3$	$3 \times 3$
		90.00 m	66%	$3 \times 3$	$3 \times 3$
		100.00 m	54%	$3 \times 3$	$3 \times 3$

Target		Duty Cycle	Measured Contrast	Simulated Contrast	Simulation Errors
Rectangular Target	No. 1	93%	0.327	0.312	4.6%
	No. 2	97%	0.341	0.328	3.8%
	No. 3	84%	0.352	0.336	4.5%
Target H		67%	0.754	0.778	3.2%
		34%	0.392	0.407	3.8%
		15%	0.254	0.243	4.3%
Target E		67%	0.779	0.805	3.3%
		39%	0.456	0.439	3.7%
		31%	0.364	0.378	3.8%
Target X		73%	0.812	0.833	2.6%
		66%	0.741	0.767	3.5%
		54%	0.586	0.608	3.7%

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Applied Optics