Acta Optica Sinica, Volume. 43, Issue 14, 1411001(2023)

Neural Radiance Field-Based Light Field Super-Resolution in Angular Domain

Yuan Miao, Chang Liu, and Jun Qiu*
Author Affiliations
  • Institute of Applied Mathematics, Beijing Information Science and Technology University, Beijing 100101, China
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    References(33)

    [1] Gershun A. The light field[J]. Journal of Mathematics and Physics, 18, 51-151(1939).

    [2] Yin Y K, Yu K, Yu C Z et al. 3D imaging using geometric light field: a review[J]. Chinese Journal of Lasers, 48, 1209001(2021).

    [3] Li J Q, Lu M L, Li Z N. Continuous depth map reconstruction from light fields[J]. IEEE Transactions on Image Processing, 24, 3257-3265(2015).

    [4] Amit Y, Felzenszwalb P, Girshick R. Object detection[M]. Ikeuchi K. Computer vision, 1-9(2020).

    [5] Boominathan V, Mitra K, Veeraraghavan A. Improving resolution and depth-of-field of light field cameras using a hybrid imaging system[C](2014).

    [6] Adelson E H, Bergen J R. The plenoptic function and the elements of early vision[J]. Computational Models of Visual Processing, 1, 3-20(1991).

    [7] Tang Y J, Wang L B, Wen G et al. Recent advances in structured illumination microscope super-resolution image reconstruction[J]. Laser & Optoelectronics Progress, 59, 0617009(2022).

    [8] Wang Z J, Zhao T Y, Hao H W et al. High-speed image reconstruction for optically sectioned, super-resolution structured illumination microscopy[J]. Advanced Photonics, 4, 026003(2022).

    [9] Wanner S, Goldluecke B. Variational light field analysis for disparity estimation and super-resolution[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 606-619(2014).

    [10] Georgiev T G, Zheng K C, Curless B et al. Spatio-angular resolution tradeoffs in integral photography[J]. Rendering Techniques, 2006, 21(2006).

    [11] Penner E, Zhang L. Soft 3D reconstruction for view synthesis[J]. ACM Transactions on Graphics, 36, 1-11(2017).

    [13] Mildenhall B, Srinivasan P P, Ortiz-Cayon R et al. Local light field fusion: practical view synthesis with prescriptive sampling guidelines[J]. ACM Transactions on Graphics, 38, 1-14(2019).

    [14] Seitz S M, Dyer C R. View morphing[C], 21-30(1996).

    [15] Levoy M, Hanrahan P. Light field rendering[C], 31-42(1996).

    [16] Yoon Y, Jeon H G, Yoo D et al. Learning a deep convolutional network for light-field image super-resolution[C], 57-65(2016).

    [17] Wang Y L, Liu F, Wang Z L et al. End-to-end view synthesis for light field imaging with pseudo 4DCNN[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11206, 340-355(2018).

    [18] Yeung H W F, Hou J H, Chen J et al. Fast light field reconstruction with deep coarse-to-fine modeling of spatial-angular clues[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11210, 138-154(2018).

    [19] Wu G C, Liu Y B, Fang L et al. Light field reconstruction using convolutional network on EPI and extended applications[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 41, 1681-1694(2019).

    [20] Xie Y B, Xu N T, Zhou S et al. Super-resolution image reconstruction of distributed infrared array camera[J]. Laser & Optoelectronics Progress, 59, 1611004(2022).

    [21] Chang Y, Gai M. A review on neural radiance fields based view synthesis[J]. Journal of Graphics, 42, 376-384(2021).

    [22] Mildenhall B, Srinivasan P P, Tancik M et al. NeRF: representing scenes as neural radiance fields for view synthesis[J]. Communications of the ACM, 65, 99-106(2022).

    [23] Vaswani A, Shazeer N, Parmar N et al. Attention is all You need[C], 6000-6010(2017).

    [24] Martin-Brualla R, Radwan N, Sajjadi M S M et al. NeRF in the wild: neural radiance fields for unconstrained photo collections[C], 7206-7215(2021).

    [26] Park K, Sinha U, Barron J T et al. Nerfies: deformable neural radiance fields[C], 5845-5854(2022).

    [27] Meng N, So H K H, Sun X et al. High-dimensional dense residual convolutional neural network for light field reconstruction[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43, 873-886(2021).

    [28] Schönberger J L, Frahm J M. Structure-from-motion revisited[C], 4104-4113(2016).

    [29] Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters, 44, 800-801(2008).

    [30] Wang Z, Bovik A C, Sheikh H R et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing, 13, 600-612(2004).

    [31] Zhang R, Isola P, Efros A A et al. The unreasonable effectiveness of deep features as a perceptual metric[C], 586-595(2018).

    [32] Honauer K, Johannsen O, Kondermann D et al. A dataset and evaluation methodology for depth estimation on 4D light fields[M]. Lai S H, Lepetit V, Nishino K, et al. Computer vision-ACCV 2016. Lecture notes in computer science, 10113, 19-34(2017).

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    Yuan Miao, Chang Liu, Jun Qiu. Neural Radiance Field-Based Light Field Super-Resolution in Angular Domain[J]. Acta Optica Sinica, 2023, 43(14): 1411001

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    Paper Information

    Category: Imaging Systems

    Received: Feb. 14, 2023

    Accepted: Mar. 24, 2023

    Published Online: Jul. 13, 2023

    The Author Email: Jun Qiu (qiujun@bistu.edu.cn)

    DOI:10.3788/AOS230549

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