[1] Cai S Z, Mémin E, Dérian P et al. Motion estimation under location uncertainty for turbulent fluid flows[J]. Experiments in Fluids, 59, 8(2017).

[2] Raffel M, Willert C E, Scarano F et al[M]. Particle image velocimetry: a practical guide(2018).

[3] Xiong J Z, Kong M, Hong B et al. Particle image velocimetry using cross-correlation optical flow algorithm based on radial basis function interpolation[J]. Chinese Journal of Lasers, 50, 0604001(2023).

[4] Law A W, Wang H W. Measurement of mixing processes with combined digital particle image velocimetry and planar laser induced fluorescence[J]. Experimental Thermal and Fluid Science, 22, 213-229(2000).

[5] Dahm W J A, Su L K, Southerland K B. A scalar imaging velocimetry technique for fully resolved four-dimensional vector velocity field measurements in turbulent flows[J]. Physics of Fluids A: Fluid Dynamics, 4, 2191-2206(1992).

[6] Seasholtz R G, Zupanc F J, Schneider S J. Spectrally resolved Rayleigh scattering diagnostic for hydrogen-oxygen rocket plume studies[J]. Journal of Propulsion and Power, 8, 935-942(1992).

[7] Stier B, Koochesfahani M M. Molecular Tagging Velocimetry (MTV) measurements in gas phase flows[J]. Experiments in Fluids, 26, 297-304(1999).

[8] Xu L H, Zhang H, Li D et al. Non-invasive measurement of blood flow velocity based on photoacoustic calorimetric measurement[J]. Chinese Journal of Lasers, 51, 0307205(2024).

[9] He W W, Yuan H C, Guo J J et al. Remote sensing monitoring method of ship exhaust based on background image reconstruction[J]. Acta Optica Sinica, 44, 1228008(2024).

[10] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

[11] Dosovitskiy A, Fischer P, Ilg E et al. FlowNet: learning optical flow with convolutional networks[C], 2758-2766(2015).

[12] Ilg E, Mayer N, Saikia T et al. FlowNet 2.0: evolution of optical flow estimation with deep networks[C], 1647-1655(2017).

[13] Sun D Q, Yang X D, Liu M Y et al. PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume[C], 8934-8943(2018).

[14] Teed Z, Deng J. RAFT: recurrent all-pairs field transforms for optical flow[M]. Computer vision‒ECCV 2020, 12347, 402-419(2020).

[15] Jiang S H, Campbell D, Lu Y et al. Learning to estimate hidden motions with global motion aggregation[C], 9752-9761(2021).

[16] Zhao B, Meng X Y, Xiao S D et al. Initial value estimation of digital image correlation method for two-dimensional deformation measurement based on GMA optical flow network[J]. Acta Optica Sinica, 43, 1310002(2023).

[17] Gu X Y, Gu X J, Ding J et al. Estimation of gas velocity in optical gas imaging based on deep optical flow network[J]. Acta Optica Sinica, 44, 1812001(2024).

[18] Dai J F, Qi H Z, Xiong Y W et al. Deformable convolutional networks[C], 764-773(2017).

[19] Dai Y M, Gieseke F, Oehmcke S et al. Attentional feature fusion[C], 3559-3568(2021).

[20] Jiang M T, Law A W, Song J. Mixing characteristics of inclined dense jets with different nozzle geometries[J]. Journal of Hydro-Environment Research, 27, 116-128(2019).

[21] Jasak H. OpenFOAM: open source CFD in research and industry[J]. International Journal of Naval Architecture and Ocean Engineering, 1, 89-94(2009).

[22] Jirka G H. Integral model for turbulent buoyant jets in unbounded stratified flows Part I: single round jet[J]. Environmental Fluid Mechanics, 4, 1-56(2004).

[23] Horn B K P, Schunck B G. Determining optical flow[J]. Artificial Intelligence, 17, 185-203(1981).

[24] Carlier J. Second set of fluid mechanics image sequences[EB/OL]. http:∥www.fluid.irisa.fr