示踪粒子光学退化图像非盲复原方法

doi:10.7527/S1000-6893.2026.33145

Abstract

Abstract:

Velocity field measurement techniques based on tracer particle imaging are widely employed in flow diagnostics. However， their application in complex flow environments is inevitably challenged by aero-optical aberrations. For instance， in combustion or supersonic/hypersonic environments， refractive index fields with drastic spatial variations induce severe aero optical effects， causing significant degradation of tracer particle images and compromising the accuracy of velocity measurements. To mitigate this issue， a novel technical approach for the non-blind restoration of degraded images of tracer particles via Singular Value Decomposition （SVD） of the Point Spread Function （PSF） is proposed. This method first performs SVD on PSFs obtained at multiple calibration positions within the field of view and subsequently reconstructs the full-field PSF distribution efficiently using a limited number of spatial modes and their corresponding spatial weighting coefficients. Furthermore， a Total Variation （TV） regularized Richardson-Lucy iterative deconvolution algorithm is employed to perform non-blind restoration on the degraded particle images using the reconstructed local PSFs. Through various numerical simulations， the influence of the number of SVD modes and image noise levels on the restoration performance is systematically investigated， and the restoration performance is compared with classical restoration algorithms. The results show that the proposed method works effectively in processing the sparse particle fields. It effectively recovers particle morphology blurred by aero-optical effects and substantially enhances the Peak Signal-to-Noise Ratio （PSNR） and Structural Similarity Index Measure （SSIM） of the images， offering a new perspective for the application of tracer-based velocimetry in harsh optical environments.

Key words: particle image velocimetry, particle tracing velocimetry, aero-optical effects, image restoration, point spread function, singular value decomposition

CLC Number:

V211.7

Huan WU, Weiran WANG, Yuan XIONG, Chong PAN, Jinjun WANG. A novel approach for non-blind restoration of optically degraded images of tracer particles[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(16): 133145.

Figures/Tables 23

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Table 1

Key parameters setting for degraded image restoring simulation experiment

参数	数值
标定PSF采样点数 $M$	49
截断SVD模态数量 $m$	1~49
RL-TV算法迭代次数 $N$	1~2 000
TV正则化参数 $λ T V$	$10 - 9$ ~ $10 - 1$
噪声水平SNR/dB	0（无噪声），10，20，30

Table 1

Fig.6

Table 2

Fig.7

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Fig.14

Fig.15

Table 3

Quantitative evaluation of restoration quality under different noise levels

SNR/dB	最优 $λ T V$ /10^-6	PSNR/dB	SSIM
10	6.14	50.25	0.992 5
20	5.34	51.78	0.995 7
30	4.98	53.25	0.997 5
0（无噪声）	0.10	54.17	0.999 8

Table 3

Fig.16

Fig.17

Fig.18

Fig.19

Table 4

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插值方法	重构误差	PSNR/dB	SSIM
双线性插值	0.059 5	37.781	0.991 7
双三次插值	0.048 9	37.464	0.991 8
样条插值	0.046 5	37.818	0.992 4

方法	运行时间/s	PSNR/dB	SSIM
分块拼接法	34.61	32.89	0.968 6
Nagy法	176.84	30.81	0.933 0
O’Connor法	167.28	30.71	0.950 4
PSF-SVD结合RL-TV	70.21	39.07	0.993 8

A novel approach for non-blind restoration of optically degraded images of tracer particles

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