Researching | Optimization Method for Underwater Scattering Imaging Based on Off-Axis Digital Holography

Laser & Optoelectronics Progress, Volume. 62, Issue 14, 1411002(2025)

Optimization Method for Underwater Scattering Imaging Based on Off-Axis Digital Holography

Quan Liu¹, Ying Jin^2,3,4、*, Quanying Wu^1、**, Weixuan Yi^2,3,4, Haofan Wang^2,3,4, and Guohai Situ^2,3,4

Author Affiliations

¹College of Physical Science and Technology, Suzhou University of Science and Technology, Suzhou 215009, Jiangsu , China

²Aerospace Laser Technology and System Department, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China

³Wangzhijiang Innovation Center for Laser, Shanghai 201800, China

⁴Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China

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References (30)

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Figures & Tables(21)

Fig. 1. Underwater off-axis digital hologram imaging

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Fig. 2. Flow chart of hologram reconstruction

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Fig. 3. Filtering schematic of 4F system

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Fig. 4. Relationship between scattering noise intensity and camera receiving angle

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Fig. 5. Frequency domain diagram of 4F pinhole filtering system

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Fig. 6. Principle of down-sampling image segmentation

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Fig. 7. Training process of image denoising

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Fig. 8. Underwater off-axis digital holographic imaging experimental setup based on 4F system

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Fig. 9. Imaging results at different attenuation lengths. (a)‒(d) Direct imaging; (e)‒(h) 4F filtered off-axis digital holography imaging

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Fig. 10. Holographic imaging with or without 4F system at different attenuation lengths. (a)‒(d) Without 4F system; (e)‒(h) with 4F system

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Fig. 11. Reconstructed holograms with or without 4F system at different attenuation lengths. (a)‒(d) Without 4F system; (e)‒(h) with 4F system

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Fig. 12. Holograms reconstructed at different light intensity ratios and attenuation lengths

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Fig. 13. Comparison of evaluation indexes of reconstructed holograms at different light intensity ratios and attenuation lengths. (a) SSIM; (b) PSNR; (c) RMSE

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Fig. 14. Holograms reconstructed by different filters at different attenuation lengths. (a) (d) Butterworth low-pass filter; (b) (e) ideal low-pass filter; (c) (f) Gaussian low-pass filter

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Fig. 15. Comparison of evaluation indexes of holograms reconstructed by different filters at different attenuation lengths. (a) SSIM; (b) PSNR; (c) RMSE

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Fig. 16. Reconstruction results at maximum attenuation length. (a) Attenuation length of 10.4; (b) attenuation length of 10.3

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Fig. 17. Noisy and denoised images. (a)(c) Reconstruction images before denoising; (b)(d) reconstructed images after denoising

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Table 1. Imaging quality evaluation indexes of direct imaging and holographic imaging at different attenuation lengths

Table 1. Imaging quality evaluation indexes of direct imaging and holographic imaging at different attenuation lengths

Attenuation length	Evaluation index
Attenuation length	Name	Fig. 9 （a）	Fig. 9 （b）	Fig. 9 （c）	Fig. 9 （d）	Fig. 9 （e）	Fig. 9 （f）	Fig. 9 （g）	Fig. 9 （h）
2.4	SSIM	0.769	0.631	0.655	0.766	0.781	0.753	0.677	0.773
	PSNR /dB	8.67	8.23	8.97	8.53	13.67	11.52	12.53	13.57
	RMSE	81.42	82.33	78.69	82.31	64.38	65.48	64.63	61.68
4.3	SSIM	0.653	0.455	0.403	0.503	0.644	0.664	0.633	0.539
	PSNR /dB	6.81	6.12	6.63	6.89	10.87	11.23	12.03	11.89
	RMSE	94.52	93.47	92.41	91.63	81.21	83.42	82.43	81.56
6.4	SSIM	0.103	0.107	0.112	0.133	0.408	0.421	0.493	0.433
	PSNR /dB	3.12	3.53	3.56	3.42	8.67	8.23	8.15	8.43
	RMSE	193.67	183.42	162.42	160.71	106.31	108.34	102.23	100.03
9.3	SSIM					0.288	0.232	0.312	0.254
	PSNR /dB					4.83	4.67	4.87	4.93
	RMSE					153.42	151.34	145.74	148.44

Table 2. Evaluation indexes of reconstructed holograms with or without 4F system at different attenuation lengths

Table 2. Evaluation indexes of reconstructed holograms with or without 4F system at different attenuation lengths

Attenuation length	Evaluation index
Attenuation length	Name	Fig. 11（a）	Fig. 11 （b）	Fig. 11 （c）	Fig. 11 （d）	Fig. 11 （e）	Fig. 11 （f）	Fig. 11 （g）	Fig. 11 （h）
2.4	SSIM	0.642	0.643	0.412	0.355	0.781	0.753	0.677	0.773
	PSNR /dB	10.71	10.82	8.61	6.23	13.67	11.52	12.53	13.57
	RMSE	88.65	86.38	102.34	123.47	64.38	65.48	64.63	61.68
4.2	SSIM	0.439	0.493	0.315	0.314	0.644	0.664	0.633	0.539
	PSNR /dB	8.96	9.34	5.65	5.61	10.87	11.23	12.03	11.89
	RMSE	106.75	102.96	115.63	122.39	81.21	83.42	82.43	81.56
6.4	SSIM	0.204	0.305	0.297	0.217	0.408	0.421	0.493	0.433
	PSNR /dB	4.13	5.32	4.78	4.67	8.67	8.23	8.15	8.43
	RMSE	151.14	159.63	166.43	175.31	106.31	108.34	102.23	100.03
8.2	SSIM	0.015	0.211	0.102	0.096	0.356	0.321	0.463	0.255
	PSNR /dB	0.97	4.22	2.14	1.75	6.13	6.67	7.13	5.03
	RMSE	220.13	216.75	200.33	207.43	126.41	122.73	117.25	128.79
9.3	SSIM	0.007	0.015	0.011	0.009	0.258	0.212	0.312	0.254
	PSNR /dB	0.31	0.83	0.77	0.67	4.83	4.67	4.87	4.93
	RMSE	217.63	211.32	213.79	215.37	133.42	151.34	145.74	148.44

Table 3. Evaluation index of reconstructed images
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Table 3. Evaluation index of reconstructed images
Attenuation length PSNR /dB SSIM RMSE
10.4 3.21 0.095 182.66
10.3 4.65 0.175 164.23

Table 4. Evaluation indexes of denoised images
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Table 4. Evaluation indexes of denoised images
Attenuation length PSNR /dB SSIM RMSE
10.4 6.53 0.265 122.53
10.3 7.68 0.377 112.74

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Quan Liu, Ying Jin, Quanying Wu, Weixuan Yi, Haofan Wang, Guohai Situ. Optimization Method for Underwater Scattering Imaging Based on Off-Axis Digital Holography[J]. Laser & Optoelectronics Progress, 2025, 62(14): 1411002

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Paper Information

Category: Imaging Systems

Received: Jan. 9, 2025

Accepted: Feb. 4, 2025

Published Online: Jul. 3, 2025

The Author Email: Ying Jin (yingjin@siom.ac.cn), Quanying Wu (wqycyh@mail.usts.edu.cn)

DOI:10.3788/LOP250473

CSTR:32186.14.LOP250473

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology