Analysis of analog correlated multiple sampling noise reduction in low noise CMOS image sensor

Chenyang Wang; Xuan Li; Xinyang Wang; Bin Huang; Cheng Ma; Yang Li; Guosong Xin

doi:10.1117/12.3030714

3 June 2024 Analysis of analog correlated multiple sampling noise reduction in low noise CMOS image sensor

Chenyang Wang, Xuan Li, Xinyang Wang, Bin Huang, Cheng Ma, Yang Li, Guosong Xin

Author Affiliations +

Proceedings Volume 13182, 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024); 1318205 (2024) https://doi.org/10.1117/12.3030714
Event: 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024), 2024, Kunming, China

Abstract

Correlated multiple sampling (CMS), an extension of correlated double sampling (CDS), is a very popular technique for denoising the readout chain of image sensors. In this paper, a mathematical readout model of CMS is established, and the readout noise is simulated. Combined with the simulation results and experiments, the influence of three CMS parameters on the noise is analyzed: number of sampling, sampling period, and the interval between the last reset sampling and the first signal sampling. The experimental results are in good agreement with the simulation results, showing how the CMS parameters affect the noise. Finally, combined with the experimental results, an optimal configuration is selected, and an ultra-low noise of 0.46e- is obtained.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chenyang Wang, Xuan Li, Xinyang Wang, Bin Huang, Cheng Ma, Yang Li, and Guosong Xin "Analysis of analog correlated multiple sampling noise reduction in low noise CMOS image sensor", Proc. SPIE 13182, 2024 International Conference on Optoelectronic Information and Optical Engineering (OIOE 2024), 1318205 (3 June 2024); https://doi.org/10.1117/12.3030714

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