Research on A/D driver circuit level nonuniformity correction technology based on machine learning

Chunhua Yang; Honglie Xu; Li Mao; Yuan Liu

doi:10.1117/12.3007620

18 December 2023 Research on A/D driver circuit level nonuniformity correction technology based on machine learning

Chunhua Yang, Honglie Xu, Li Mao, Yuan Liu

Proceedings Volume 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics; 1296310 (2023) https://doi.org/10.1117/12.3007620
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China

Abstract

A non-uniformity correction method based on machine learning for A/D driver circuit level. Firstly, different types of infrared detectors are placed in a temperature uniform radiation field. When they are working normally, the analog output signal waveform of each detector in multiple scenarios is collected multiple times to obtain the approximate average voltage value of each line in a frame, and saved as a document; Secondly, using GPU for machine learning of the above documents and accurately driving the D/A chip for digital to analog conversion, simulating the waveform voltage value of the analog output signal mentioned above to generate waveform voltage with similar nonuniformity; Thirdly, the voltage waveform generated by the multi-channel voltage output digital to analog converter is followed by an operational amplifier, filtered, and then output to the A/D chip as the reference voltage for sampling; Finally, the analog video signal output by the infrared detector is sampled and quantized by an A/D chip to obtain a more uniform image digital signal.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chunhua Yang, Honglie Xu, Li Mao, and Yuan Liu "Research on A/D driver circuit level nonuniformity correction technology based on machine learning", Proc. SPIE 12963, AOPC 2023: Optical Sensing, Imaging, and Display Technology and Applications; and Biomedical Optics, 1296310 (18 December 2023); https://doi.org/10.1117/12.3007620

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