Retained imaging quality with reduced manufacturing precision: leveraging computational optics

Yujie Xing; Xiong Dun; Dinghao Yang; Siyu Dong; Yifan Peng; Xuquan Wang; Jun Yu; Zhanshan Wang; Xinbin Cheng

doi:10.1117/1.APN.4.4.046014

Advanced Photonics Nexus, Volume. 4, Issue 4, 046014(2025)

Retained imaging quality with reduced manufacturing precision: leveraging computational optics

Yujie Xing^1,2,3, Xiong Dun^1,2,3、*, Dinghao Yang^1,2,3, Siyu Dong^1,2,3, Yifan Peng⁴, Xuquan Wang^1,2,3、*, Jun Yu^1,2,3、*, Zhanshan Wang^1,2,3,5, and Xinbin Cheng^1,2,3,5

Author Affiliations

¹Tongji University, Institute of Precision Optical Engineering, School of Physics Science and Engineering, Shanghai, China

²MOE Key Laboratory of Advanced Micro-Structured Materials, Shanghai, China

³Shanghai Frontiers Science Center of Digital Optics, Shanghai, China

⁴The University of Hong Kong, Department of Electrical and Electronic Engineering, Hong Kong, China

⁵Tongji University, Shanghai Institute of Intelligent Science and Technology, Shanghai, China

show less

References(49)

[1] et alMetasurface-based computational imaging: a review. Adv. Photonics, 6, 014002(2024). https://doi.org/10.1117/1.AP.6.1.014002

[2] et alDesign, fabrication and assembly of the solar upper transition region imager (SUTRI). Res. Astron. Astrophys., 23, 095009(2023). https://doi.org/10.1088/1674-4527/ace17b

[3] et alEnd-to-end deep learning framework for digital holographic reconstruction. Adv. Photonics, 1, 016004(2019). https://doi.org/10.1117/1.AP.1.1.016004

[4] et alDesign and demonstration of airborne imaging system for target detection based on area array camera and push-broom hyperspectral imager. Infrared Phys. Technol., 116, 103794(2021). https://doi.org/10.1016/j.infrared.2021.103794

[5] et alCooled and uncooled infrared detectors for missile seekers. Proc. SPIE, 9070, 90700P(2014). https://doi.org/10.1117/12.2050099

[6] Optical design of dual-mode seeker for long-wave infrared and mid-wave infrared seeker in missile application. Proc. SPIE, 10743, 107430I(2018). https://doi.org/10.1117/12.2320982

[7] et alImaging infrared seeker design and tests for FOK guided missile. Proc. SPIE, 12533, 125330Z(2023). https://doi.org/10.1117/12.2665111

[8] et alMeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance, 360-369(2007). https://doi.org/10.1109/IPSN.2007.4379696

[9] et alMoving human detection and tracking from thermal video through intelligent surveillance system for smart applications. Multimedia Tools Appl., 82, 39551-39570(2023). https://doi.org/10.1007/s11042-022-13515-6

[10] et alFreeform spectrometer enabling increased compactness. Light: Sci. Appl., 6, e17026-e17026(2017). https://doi.org/10.1038/lsa.2017.26

[11] et alFreeform optics for imaging. Optica, 8, 161-176(2021). https://doi.org/10.1364/OPTICA.413762

[12] et alZoom lens with high zoom ratio design based on Gaussian bracket and particle swarm optimization. Appl. Opt., 60, 3217-3223(2021). https://doi.org/10.1364/AO.418970

[13] et alAccuracy verification methodology for computer generated hologram used for testing a 3.5-meter mirror based on an equivalent element. Light: Adv. Manuf., 5, 195-203(2024). https://doi.org/10.37188/lam.2024.025

[14] et alOptics technology for large-aperture space telescopes: from fabrication to final acceptance tests. Adv. Opt. Photonics, 10, 644-702(2018). https://doi.org/10.1364/AOP.10.000644

[15] et alTolerance analysis of hyper numerical aperture lithography objective with freeform surfaces. Proc. SPIE, 10827, 108272C(2018). https://doi.org/10.1117/12.2501037

[16] et alChallenges and strategies in high accuracy manufacturing of the world’s largest SiC aspheric mirror. Light: Sci. Appl., 11, 310(2022). https://doi.org/10.1038/s41377-022-00994-3

[17] Sensitivity control to surface irregularity. Proc. SPIE, 6342, 634225(2006). https://doi.org/10.1117/12.692246

[18] et alDesign method for freeform reflective-imaging systems with low surface figure error sensitivity. Chinese Opt. Lett., 17, 092201(2019). https://doi.org/10.3788/COL201917.092201

[19] et alCorrective optics space telescope axial replacement alignment system. Proc. SPIE, 1996, 193-204(1993). https://doi.org/10.1117/12.160414

[20] et alFreeform surface compensation design for machining error of primary mirror. Proc. SPIE, 12617, 1261775(2023). https://doi.org/10.1117/12.2666802

[21] et alComputational optics for mobile terminals in mass production. IEEE Trans. Pattern Anal. Mach. Intell., 45, 4245-4259(2022). https://doi.org/10.1109/TPAMI.2022.3200725

[22] et alMobile image restoration via prior quantization. Pattern Recognit. Lett., 174, 64-70(2023). https://doi.org/10.1016/j.patrec.2023.08.017

[23] Practical method of cost-based tolerancing. Proc. SPIE, 8491, 849105(2012). https://doi.org/10.1117/12.928179

[24] et alPost optical freeform compensation technique for machining errors of large-aperture primary mirror. Photonics, 10, 768(2023). https://doi.org/10.3390/photonics10070768

[25] et alCompensating lens designs and testing of the COSTAR optics, 278-284(1994). https://doi.org/10.1364/IODC.1994.TSO.284

[26] et alThe Hubble Space Telescope optical systems failure report(1990).

[27] et alDeep learning phase recovery: data-driven, physics-driven, or a combination of both?. Adv. Photonics Nexus, 3, 056006(2024). https://doi.org/10.1117/1.APN.3.5.056006

[28] et alLearned large field-of-view imaging with thin-plate optics. ACM Trans. Graph., 38, 219-234(2019). https://doi.org/10.1145/3355089.3356526

[29] et alReal-time high-quality single-lens computational imaging via enhancing lens modulation transfer function consistency. Opt. Express, 33, 5179-5190(2025). https://doi.org/10.1364/OE.552050

[30] et alLearned multi-aperture color-coded optics for snapshot hyperspectral Iimaging. ACM Trans. Graph., 43, 1-11(2024). https://doi.org/10.1145/3687976

[31] et alShift-variant color-coded diffractive spectral imaging system. Optica, 8, 1424-1434(2021). https://doi.org/10.1364/OPTICA.439142

[32] et alExtreme-quality computational imaging via degradation framework, 2632-2641(2021). https://doi.org/10.1109/ICCV48922.2021.00263

[33] et alDeep learning for fast spatially varying deconvolution. Optica, 9, 96-99(2022). https://doi.org/10.1364/OPTICA.442438

[34] et alGeneralized aberration regularization in the single-lens computational imaging system design. Opt. Lett., 48, 5439-5442(2023). https://doi.org/10.1364/OL.503972

[35] et alFast non-blind deconvolution via regularized residual networks with long/short skip-connections, 1-10(2017). https://doi.org/10.1109/ICCPHOT.2017.7951480

[36] et alHybrid design scheme for enabling large-aperture diffractive achromat imaging. Opt. Express, 32, 28402-28412(2024). https://doi.org/10.1364/OE.525558

[37] et alAchromatic and athermal catadioptric long wave infrared freeform prism with a diffractive surface. Infrared Phys. Technol., 123, 104207(2022). https://doi.org/10.1016/j.infrared.2022.104207

[38] et alComprehensive performance domain tolerance analysis methodology for freeform imaging spectrometers. Opt. Express, 32, 14405-14419(2024). https://doi.org/10.1364/OE.519818

[39] et alOptical aberrations correction in postprocessing using imaging simulation. ACM Trans. Graph., 40, 192(2021). https://doi.org/10.1145/3474088

[40] et alRevealing the preference for correcting separated aberrations in joint optic-image design. Opt. Lasers Eng., 178, 108220(2024). https://doi.org/10.1016/j.optlaseng.2024.108220

[41] et alDR-UNet: dynamic residual UNet for blind correction of optical degradation. Proc. SPIE, 12565, 125651B(2023). https://doi.org/10.1117/12.2662187

[42] et alUniversal and flexible optical aberration correction using deep-prior based deconvolution, 2613-2621(2021). https://doi.org/10.1109/ICCV48922.2021.00261

[43] et alHigh-quality computational imaging through simple lenses. ACM Trans. Graph., 32, 149(2013). https://doi.org/10.1145/2516971.2516974

[44] et alBlind optical aberration correction by exploring geometric and visual priors, 1684-1692(2015). https://doi.org/10.1109/CVPR.2015.7298777

[45] et alA database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, 2, 416-423(2001). https://doi.org/10.1109/ICCV.2001.937655

[46] et alPractical Poissonian-Gaussian noise modeling and fitting for single-image raw-data. IEEE Trans. Image Process., 17, 1737-1754(2008). https://doi.org/10.1109/TIP.2008.2001399

[47] et alLearned rotationally symmetric diffractive achromat for full-spectrum computational imaging. Optica, 7, 913-922(2020). https://doi.org/10.1364/OPTICA.394413

[48] et alEfficient filter flow for space-variant multiframe blind deconvolution(2010). https://doi.org/10.1109/CVPR.2010.5540158

[49] et alFast approximations of shift-variant blur. Int. J. Comput. Vision, 115, 253-278(2015). https://doi.org/10.1007/s11263-015-0817-x

Tools

Get Citation

Copy Citation Text

Yujie Xing, Xiong Dun, Dinghao Yang, Siyu Dong, Yifan Peng, Xuquan Wang, Jun Yu, Zhanshan Wang, Xinbin Cheng, "Retained imaging quality with reduced manufacturing precision: leveraging computational optics," Adv. Photon. Nexus 4, 046014 (2025)

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Research Articles

Received: Mar. 4, 2025

Accepted: Jun. 23, 2025

Published Online: Jul. 25, 2025

The Author Email: Xiong Dun (dunx@tongji.edu.cn), Xuquan Wang (wangxuquan@tongji.edu.cn), Jun Yu (yujun-88831@tongji.edu.cn)

DOI:10.1117/1.APN.4.4.046014

CSTR:32397.14.1.APN.4.4.046014

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology