Image Noise Simulation and Verification of Area Array CMOS Sensor

Jingyuan Chen; Xiao Liu; Lili Du; Bo Song; Xiaobing Sun

doi:10.3788/AOS240581

Acta Optica Sinica, Volume. 44, Issue 12, 1228007(2024)

Image Noise Simulation and Verification of Area Array CMOS Sensor

Jingyuan Chen^1,2, Xiao Liu², Lili Du², Bo Song², and Xiaobing Sun^2、*

Author Affiliations

¹University of Science and Technology of China, Hefei 230026, Anhui , China

²Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui , China

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Figures & Tables(15)

Fig. 1. Schematic of area array CMOS camera operation

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Fig. 2. Signal conversion process and noise source of CMOS sensor

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Fig. 3. Flow chart of noise model parameter calibration

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Fig. 4. Schematic of experimental system

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Fig. 5. Estimation of sensor gain $K_{a}$

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Fig. 6. Gaussian distribution probability plot of camera row noise data

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Fig. 7. Tukey lambda distribution PPCC plot of read noise

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Fig. 8. Fitting results of probability plot of read noise data distribution. (a) Fitting results of Tukey lambda distribution; (b) fitting results of Gaussian distribution

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Fig. 9. Real shot image with 10% saturation in grayscale and simulated image using model B. (a) Real shot image; (b) simulated image

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Fig. 10. Aerial image of R channel

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Fig. 11. Aerial images with photon shot noise. (a) Photon shot noise with a gain set to 5; (b) photon shot noise with a gain set to 20

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Fig. 12. Aerial images with row noise. (a) Row noise with a scale parameter set to 8; (b) row noise with a scale parameter set to 16

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Fig. 13. Aerial images with read noise when DC component is 200 and shape parameter is -0.164. (a) Read noise with a scale parameter set to 1.5; (b) read noise with a scale parameter set to 4.8

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Table 1. Results of noise parameter calibration
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Table 1. Results of noise parameter calibration
Noise parameter Value
Analog gain $K_{a}$ 1.410
Digital gain $K_{d}$ 4
DC noise component $μ_{c}$ 101.318
Shape $λ$ -0.164
Scale $σ_{Τ L}$ 2.126
Scale $σ_{r}$ 0.200

Table 2. Comparison of SNR, PSNR, and SSIM between real captured images and simulated images with two different noise models

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Table 2. Comparison of SNR, PSNR, and SSIM between real captured images and simulated images with two different noise models

Saturation value /%		10	25	45	60
SNR	Real value	40.299	53.776	79.152	83.311
	Emulation value of model A	38.036	56.858	73.875	81.962
	Emulation value of model B	39.076	56.856	74.320	82.602
Relative deviation of SNR /%	Model A	5.616	5.421	6.667	1.619
Relative deviation of SNR /%	Model B	3.035	5.417	6.105	0.851
PSNR /dB	Real value	51.169	51.144	51.148	51.194
	Emulation value of model A	50.787	51.700	50.143	51.744
	Emulation value of model B	51.490	51.695	51.761	51.765
Relative deviation of PSNR /%	Model A	0.747	1.075	1.965	1.063
Relative deviation of PSNR /%	Model B	0.623	1.066	1.184	1.103
SSIM	Real value	0.991	0.987	0.975	0.969
	Emulation value of model A	0.984	0.977	0.956	0.943
	Emulation value of model B	0.987	0.978	0.957	0.948
Relative deviation of SSIM /%	Model A	0.706	1.013	1.949	2.683
Relative deviation of SSIM /%	Model B	0.404	0.912	1.846	2.167

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Jingyuan Chen, Xiao Liu, Lili Du, Bo Song, Xiaobing Sun. Image Noise Simulation and Verification of Area Array CMOS Sensor[J]. Acta Optica Sinica, 2024, 44(12): 1228007

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