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The Method and Implementation of Temperature Drift Self-compensation for 4T CIS Based on FPGA

Published: 15 March 2023 Publication History

Abstract

In this paper, a temperature drift self-compensation method for 4T CMOS image sensor based on FPGA is designed to solve the problems of pixel drift rise and image noise caused by temperature change. This method can automatically extract the compensation coefficient of temperature drift, compensate the difference and adjust the dynamic range, so as to suppress the noise effect of temperature on image data. The experimental results show that the temperature drift self-compensation method has a good compensation effect. The checkerboard simulation reduces the mean value of the image by 14.63%, the peak signal-to-noise ratio is relatively stable, and the average gradient is increased by about 21%, which effectively weakens the influence of temperature on image brightness and detail clarity. It can be proved that the proposed method provides a reliable guarantee for the application of 4T CMOS image sensor in the space field under high temperature environment.

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EITCE '22: Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering
October 2022
1999 pages
ISBN:9781450397148
DOI:10.1145/3573428
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 March 2023

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Author Tags

  1. CMOS image sensor
  2. FPGA implementation
  3. difference compensation
  4. dynamic range adjustment

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EITCE 2022

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Overall Acceptance Rate 508 of 972 submissions, 52%

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