METHODS OF COMPENSATION OF MICROBOLOMETER MATRIСES SELF-HEATING IN THE PROCESSING OF THERMAL IMAGES
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Abstract
The sources of noise and artifacts arising during thermal imaging and the methods for thermal images filtering, including methods specific for processing of images generated by infrared sensors, are considered. In particular, distortions caused by the process of microbolometrer matrices self-heating due to internal and external heating sources and the methods for compensating such distortions are studied. The purpose of the study is to create a mathematical model of a bolometric matrix self-heating based on heat transfer equations and to develop an algorithm for suppressing of distortions introduced into thermal images by self-heating. The exponential models describing the propagation of heat in the microbolometer matrix are proposed and it is shown that the coefficients of the models after logarithming can be determined by the least squares method. For real thermal images, the coefficients of the model are determined, and situations are considered when the base temperature of the object is known and when it is necessary to restore it, and modifications of the exponential model in the form of an exponent from a complete and incomplete square are proposed. Computer simulation of the proposed distortion compensation algorithm has been carried out, a set of thermal images before and after processing has been presented, and a quantitative estimation of the degree of noise suppression caused by heating of bolometric arrays has been obtained. Based on the results of the work, it was determined that the exponential model provides a sufficient degree of closeness of the experimental and theoretically predicted temperature data, and the degree of difference between the data and the model was estimated. Recommendations are developed for the application of the proposed methods at known and unknown base temperature of the matrix. Proposals have been developed for further improving the mathematical model, including the situation of temperature changes over time, and for improving the efficiency of self-heating noise suppression algorithms.
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Zuev А. (2018), “The method of primary processing of thermograms obtained using small-size thermal imagers”, Advanced Information Systems, Vol 2, No. 4, pp. 136 – 140, DOI: https://doi.org/10.20998/2522-9052.2018.4.23.
Zheng, L. & Yi, R. (2009), “Fault diagnosis system for the inspection robot in power transmission lines maintenance”, Proc. SPIE 7513. International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Process Technology, DOI: https://doi.org/10.1117/12.837984.
Stockton, G.R. & Tache, A. (2006), “Advances in applications for aerial infrared thermography”, Proc. SPIE 6205 (Thermosense XXVIII), April 2006, DOI: https://doi.org/10.1117/12.669513.
Qin, L., Chen, S., Gao, Q. & Yi X. (2000), “Inspection for electric power systems using uncooled infrared camera”, Proc. 25th International Conference on Infrared and Millimeter Waves, Conference Digest, pp. 441-442. DOI: https://doi.org/10.1109/ICIMW.2000.893097.
Salami, A.M., Salih, D.N. & Fadhil, A.F. (2021), “Thermal Image Features and Noise Effects Analysis”, 2021 7th International Engineering Conference “Research & Innovation amid Global Pandemic" (IEC), DOI: https://doi.org/10.1109/IEC52205.2021.9476100.
de Vries, J. (2014), “Quantitative analysis and image processing techniques of large-scale industrialsize fire tests using infrared thermography”, 12th International Conference on Quantitative Infrared Thermography (QIRT 2014), France, Bordeaux, 7 - 11 July 2014, DOI: https://doi.org/10.21611/qirt.2014.042.
Sheinin, M., Schechner, Y. Y. & Kutulakos, K. N. (2018), “Rolling shutter imaging on the electric grid”, 2018 IEEE Int. Conf. on Computational Photography (ICCP), pp. 1–12. DOI: https://doi.org/10.1109/ICCPHOT.2018.8368472.
Gavriloaia, B-M., Vizireanu, R-C. & Neamtu, C. M. (2013), “An Improved Method for IR Image Filtering from Living Beings”, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3395-3398, DOI: https://doi.org/10.1109/EMBC.2013.6610270.
Restrepo, A. D. & Loaiza-Correa, H. (2016), “Background Thermal Compensation by Filtering for Contrast Enhancement in Active Thermography”, Journal of Nondestructive Evaluation, 2016, Vol. 35, is. 1, DOI: https://doi.org/10.1007/s10921-016-0336-x.
Chih-Lung, Lin, Chih-Wei, Kuo, Chih-Chin, Lai & Ming-dar, Tsa (2011), “A novel approach to fast noise reduction of infrared image”, Infrared Physics & Technology, Vol. 54, is. 1, pp. 1-9, DOI: https://doi.org/10.1016/j.infrared.2010.09.007.
Kondratov, P., Oganesyan, A., Tkachenko, V., Prudyus, I., Lazko, L. & Mymrikov, D. (2016), “Thermal images improving based on cumulative histogram correction and median filtering methods”, 2016 13th Int. Conf. on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET), DOI: https://doi.org/10.1109/TCSET.2016.7452170.
Ashiba, H. I., Mansour, H. M. & Dessouky, M. I. (2019), “Enhancement of IR images using histogram processing and the undecimated additive wavelet transform”, Multimedia Tools and Applications, Vol. 78, is/ 9, pp. 11277–11290, DOI: https://doi.org/10.1007/s11042-018-6545-9.
Bieszczad, G., Kastek, M. & Barela, J. (2011), “Image processing module for high-speed thermal camera with cooled detector”, Proc. of SPIE - The Int, Society for Optical Engineering, May 2011, DOI: https://doi.org/10.1117/12.883914.
Bieszczad, G. (2016), “SoC-FPGA embedded system for real-time thermal image processing”, MIXDES 2016, 23rd Int. Conf. "Mixed Design of Integrated Circuits and Systems", pp. 469-473, DOI: https://doi.org/10.1109/MIXDES.2016.7529788.
Bieszczad, G., Orzanowski, T., Sosnowski, T. & Kastek, M. (2009), “Method of detectors offset correction in thermovision camera with uncooled microbolometric focal plane array”, Proceedings of SPIE - The International Society for Optical Engineering, September 2009, DOI: https://doi.org/10.1117/12.830678.
Bieszczad, G. & Kastek, M. (2011), “Measurement of Thermal Behavior of Detector Array Surface with the Use of Microscopic Thermal Camera”, Metrology and Measurement Systems, January 2011, DOI: https://doi.org/10.2478/v10178-011-0064-6.
Zhigang, Fan, Haili, Hu, Wang, Zhang, Jianjun, Liu & Shouqian Chen (2012), “Self-thermal Radiation Compensation for Autofocus Algorithm in Infrared Optical System”, 2012 5th International Congress on Image and Signal Processing (CISP 2012), pp. 1330-1334, DOI: https://doi.org/10.1109/CISP.2012.6469680.
Wolf, A. & Pezoa, J. E., Figueroa M. (2016), “Modeling and Compensating Temperature-Dependent Non-Uniformity Noise in IR Microbolometer Cameras”, Sensors, Vol. 16, is. 7, 1121, DOI: https://doi.org/10.3390/s16071121.
Kumar, K. S. (2014), “Analytical Modeling of Temperature Distribution, Peak Temperature, Cooling Rate and Thermal Cycles in a Solid Work Piece Welded By Laser Welding Process”, 3rd Int. Conf. on Materials Proc. and Char/ (ICMPC 2014), pp. 821-834, DOI: https://doi.org/10.1016/j.mspro.2014.07.0.