Citation: | Lu Xiaotian, Yang Tianming, Jin Weiqi, Liu Jing, Wen Renjie. Correction methods for water fluctuation and underwater turbulence degraded imaging[J]. Journal of Applied Optics, 2017, 38(1): 42-55. DOI: 10.5768/JAO201738.0102002 |
[1] |
Efros A, Isler V, Shi J, et al. Seeing through water[J]. Advances in Neural Information Processing Systems, 2005, 17: 393-400. http://d.old.wanfangdata.com.cn/Periodical/zgmtjjxyxb200704024
|
[2] |
Fried D L. Probability of getting a lucky short-exposure image through turbulence[J]. JOSA, 1978, 68(12): 1651-1657. doi: 10.1364/JOSA.68.001651
|
[3] |
Kanaev A V, Hou W, Woods S. Multi-frame underwater image restoration[C]//SPIE Security Defence. New York: International Society for Optics and Photonics, 2011: 81850O-81850O-8. doi: 10.1117/12.898914.short?SSO=1
|
[4] |
Kanaev A V, Hou W, Woods S, et al. Restoration of turbulence degraded underwater images[J]. Optical Engineering, 2012, 51(5): 057007-1-057007-9. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=1e3cb3cb0fe0d1653c18e6dadbd8872b
|
[5] |
Kanaev A V, Hou W, Restaino S R, et al. Correction methods for underwater turbulence degraded imaging[C]//SPIE Remote Sensing. New York: International Society for Optics and Photonics, 2014: 92421P-92421P-9. doi: 10.1117/12.2066479.short
|
[6] |
Kanaev A V, Hou W, Restaino S R, et al. Restoration of images degraded by underwater turbulence using structure tensor oriented image quality (STOIQ) metric[J]. Optics Express, 2015, 23(13): 17077-17090. doi: 10.1364/OE.23.017077
|
[7] |
Vorontsov M A, Carhart G W. Anisoplanatic imaging through turbulent media: image recovery by local information fusion from a set of short-exposure images[J]. JOSA A, 2001, 18(6): 1312-1324. doi: 10.1364/JOSAA.18.001312
|
[8] |
Oreifej O, Shu G, Pace T, et al. A two-stage reconstruction approach for seeing through water[C]//Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on. New York: IEEE, 2011: 1153-1160. https: //www.researchgate.net/publication/224254791_A_Two-Stage_Reconstruction_Approach_for_Seeing_Through_Water
|
[9] |
Rueckert D, Sonoda L I, Hayes C, et al. Nonrigid registration using free-form deformations: application to breast MR images[J]. Medical Imaging, IEEE Transactions on, 1999, 18(8): 712-721. doi: 10.1109/42.796284
|
[10] |
李雄飞, 张存利, 李鸿鹏, 等.医学图像配准技术进展[J].计算机科学, 2010, 37(7): 27-33. doi: 10.3969/j.issn.1002-137X.2010.07.006
Li Xiongfei, Zhang Cunli, Li Hongpeng, et al. Development of medical image registration technology[J]. Computer Science, 2010, 37(7): 27-33. doi: 10.3969/j.issn.1002-137X.2010.07.006
|
[11] |
王伟, 苏志勋.基于移动最小二乘法的医学图像配准[J].计算机科学, 2010, 37(9): 270-271. doi: 10.3969/j.issn.1002-137X.2010.09.067
Wang Wei, Su Zhixun. Medical image registration based on moving least squares[J]. Computer Science, 2010, 37(9): 270-271. doi: 10.3969/j.issn.1002-137X.2010.09.067
|
[12] |
李磊, 王庆, 肖照林.一种基于视频的水下场景复原算法[J].系统仿真学报, 2012, 24(1):188-191. http://d.old.wanfangdata.com.cn/Conference/7571365
Li Lei, Wang Qing, Xiao Zhaolin. Underwanter image restoration algorithm from distorted video[J]. Journal of System Simulation, 2012, 24(1):188-191. http://d.old.wanfangdata.com.cn/Conference/7571365
|
[13] |
Donate A, Ribeiro E. Advances in computer graphics and computer vision[M]. Berlin: Springer Berlin Heidelberg, 2007: 264-277.
|
[14] |
张志强.一种对扭曲景象序列三维重建迭代方法[J].软件, 2013, 34(10): 100-105. doi: 10.3969/j.issn.1003-6970.2013.10.035
Zhang Zhiqiang. A method to perform 3D reconstruction on distorted image serie[J]. Software, 2013, 34(10): 100-105. doi: 10.3969/j.issn.1003-6970.2013.10.035
|
[15] |
Yang B, Zhang W, Xie Y, et al. Distorted image restoration via non-rigid registration and lucky-region fusion approach[C]//Information Science and Technology (ICIST), 2013 International Conference on. New York: IEEE, 2013: 414-418. https: //www.researchgate.net/publication/283486917_Distorted_image_restoration_via_non-rigid_registration_and_lucky-region_fusion_approach
|
[16] |
杨波, 张文生, 谢源.畸变环境下的序列图像融合技术研究[J].计算机科学, 2013, 40(10): 261-264. doi: 10.3969/j.issn.1002-137X.2013.10.055
Yang Bo, Zhang Wensheng, Xie Yuan. Research on distortion-free fusion of sequence images[J]. Computer Science, 2013, 40(10): 261-264. doi: 10.3969/j.issn.1002-137X.2013.10.055
|
[17] |
Halder K K, Tahtali M, Anavatti S G. High accuracy image restoration method for seeing through water[C]//SPIE Optical Engineering Applications. New York: International Society for Optics and Photonics, 2014: 921702-921702-6. https: //www.researchgate.net/publication/269098153_High_Accuracy_Image_Restoration_Method_for_Seeing_through_Water
|
[18] |
Hua W, Xiea Y, Zhanga W, et al. Removing water fluctuation via motion field-based Kernel regression?[J]. Journal of Information & Computational Science, 2014, 11(15):5289-5296. http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0235032165/
|
[19] |
Tian Y, Narasimhan S G. Seeing through water: Image restoration using model-based tracking[C]//Computer Vision, 2009 IEEE 12th International Conference on. New York: IEEE, 2009: 2303-2310. https: //www.researchgate.net/publication/224136114_Seeing_through_water_Image_restoration_using_model-based_tracking
|
[20] |
Tian Y, Narasimhan S G. A globally optimal data-driven approach for image distortion estimation[C]//Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. New York: IEEE, 2010: 1277-1284. https: //www.researchgate.net/publication/221361890_A_Globally_Optimal_Data-Driven_Approach_for_Image_Distortion_Estimation
|
[21] |
Tian Y, Narasimhan S G. Globally optimal estimation of nonrigid image distortion[J]. International Journal of Computer Vision, 2012, 98(3): 279-302. doi: 10.1007/s11263-011-0509-0
|
[22] |
Wen Z, Lambert A, Fraser D, et al. Bispectral analysis and recovery of images distorted by a moving water surface[J]. Applied Optics, 2010, 49(33): 6376-6384. doi: 10.1364/AO.49.006376
|
[23] |
Halder K K, Tahtali M, Anavatti S G. Artificial intelligence: methods and applications[M]. Berlin: Springer International Publishing, 2014: 384-394.
|
[24] |
Zhang M, Lin X, Gupta M, et al. Computer vision-ECCV 2014[M]. Berlin: Springer International Publishing, 2014: 234-250.
|
[25] |
Seemakurthy K, Rajagopalan A N. Deskewing of underwater images[J]. Image Processing, IEEE Transactions on, 2015, 24(3): 1046-1059. doi: 10.1109/TIP.2015.2395814
|
[26] |
McGlamery B L. A computer model for underwater camera systems[J]. SPIE Ocean Optics, 1979, 208: 221-231. https://www.researchgate.net/publication/244953801_A_Computer_Model_For_Underwater_Camera_Systems
|
[27] |
Jaffe J S.Computer modeling and the design of optimal underwaterimagingsystems[J]. IEEE Journal of Oceanic Engineering, 1990, 15(2): 101-111. doi: 10.1109/48.50695
|
[28] |
Trucco E, Olmos-Antillon A T. Self-tuning underwater image restoration[J]. IEEE Journal of Oceanic Engineering, 2006, 31(2): 511-519. doi: 10.1109/JOE.2004.836395
|
[29] |
Sanchez-Ferreira C, Ayala H V H, Coelho L S. Multi-objective differential evolution algorithm for underwater image restoration[C]//2015 IEEE Congress on Evolutionary Computation. New York: IEEE, 2015: 243-250 https: //www.researchgate.net/publication/301287353_Multi-objective_differential_evolution_algorithm_for_underwater_image_restoration
|
[30] |
Hou W, Weidemann A D. Objectively assessing underwater image quality for the purpose of automated restoration[C]//Defense and Security Symposium. New York: International Society for Optics and Photonics, 2007: 65750Q-65750Q-7. https: //www.researchgate.net/publication/235125922_Objectively_Assessing_Underwater_Image_Quality_for_the_Purpose_of_Automated_Restoration
|
[31] |
Hou W, Woods S, Goode W, et al. Impacts of optical turbulence on underwater imaging[C]//SPIE Defense, Security, and Sensing. New York: International Society for Optics and Photonics, 2011: 803009-803009-7. https: //www.researchgate.net/publication/253507134_Impacts_of_optical_turbulence_on_underwater_imaging
|
[32] |
Hou W W. A simple underwater imaging model[J]. Optics Letters, 2009, 34(17): 2688-2690. doi: 10.1364/OL.34.002688
|
[33] |
Hou W, Woods S, Jarosz E, et al. Optical turbulence on underwater image degradation in natural environments[J]. Applied Optics, 2012, 51(14): 2678-2686. doi: 10.1364/AO.51.002678
|
[34] |
Hou W, Goode W, Kanaev A. Underwater image quality degradation by scattering[C]//OCEANS, 2012-Yeosu. New York: IEEE, 2012: 1-5. https: //ieeexplore.ieee.org/document/6263409
|
[35] |
Sun D, Roth S, Black M J. Secrets of optical flow estimation and their principles[C]//Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. New York: IEEE, 2010: 2432-2439. https: //www.researchgate.net/publication/221364345_Secrets_of_Optical_Flow_Estimation_and_Their_Principles
|
[36] |
Brox T, Bruhn A, Papenberg N, et al. High accuracy optical flow estimation based on a theory for warping[C]//European Conference on Computer Vision. Berlin: Springer Berlin Heidelberg, 2004: 25-36. doi: 10.1007%2F978-3-540-24673-2_3
|
[37] |
Lin Z, Chen M, Ma Y. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices[J/OL]. arXiv, 2010, 1009:5055. http://d.old.wanfangdata.com.cn/OAPaper/oai_arXiv.org_1009.5055
|
[38] |
Rueckert D, Sonoda L I, Hayes C, et al. Nonrigid registration using free-form deformations: application to breast MR images[J]. IEEE Transactions on Medical Imaging, 1999, 18(8): 712-721. doi: 10.1109/42.796284
|
[1] | HE Sijie, DAI Caihong, CHENG Qiutong, WU Zhifeng, LI Ling, WANG Yanfei. Influence of field of view angle and positioning error on spectral radiance measurement[J]. Journal of Applied Optics, 2023, 44(2): 386-391. DOI: 10.5768/JAO202344.0203004 |
[2] | MA Dazhi, YU Binchao, ZHANG Yanze, LIU Wei, YUE Yi, YANG Jizhi, CHEN Qintao. Measurement system of large-scale high reflective component based on binocular vision[J]. Journal of Applied Optics, 2021, 42(4): 577-585. DOI: 10.5768/JAO202142.0401002 |
[3] | ZHU Wenjie, LING He, YANG Shoupeng. Research on compensation for positioning errors of carbody welding points based on binocular vision[J]. Journal of Applied Optics, 2021, 42(1): 79-85. DOI: 10.5768/JAO202142.0102005 |
[4] | CUI Enkun, TENG Yanqing, LIU Jiawei. Calibration error compensation technique of stereoscopic vision measurement system[J]. Journal of Applied Optics, 2020, 41(6): 1174-1180. DOI: 10.5768/JAO202041.0601006 |
[5] | HAO Renjie, WANG Zhongyu, LI Yaru. Error analysis method for monocular vision pose measurement system[J]. Journal of Applied Optics, 2019, 40(1): 79-85. DOI: 10.5768/JAO201940.0103001 |
[6] | Zhang Jianlong, Pan Xin, He Lei, Yang Zhen, Guo Xinmin, Kang Weimin. Error analysis of optical system for full-view and high-precision three-dimensional measuring instrument[J]. Journal of Applied Optics, 2018, 39(3): 392-399. DOI: 10.5768/JAO201839.0303004 |
[7] | Miao Lijun, Che Ziyuan. Visual locating of mobile robot based on adaptive down sampling[J]. Journal of Applied Optics, 2017, 38(3): 429-433. DOI: 10.5768/JAO201738.0302008 |
[8] | Wang Qiyue, Wang Zhongyu. Position and pose measurement of spacecraft based on monocular vision[J]. Journal of Applied Optics, 2017, 38(2): 250-255. DOI: 10.5768/JAO201738.0203001 |
[9] | Peng Fu-lun, Wang Jing, Wu Yi-lei, Guo Cheng. Object positioning and error analysis of vehicular electro-optical reconnaissance system[J]. Journal of Applied Optics, 2014, 35(4): 557-562. |
[10] | DU Jun-feng. Error budget design for photoelectric theodolite[J]. Journal of Applied Optics, 2006, 27(6): 506-509. |
1. |
刘维慧,梁润泽,赵泉昕,卓朝博,苗永平. 双光源干涉法测量液态薄膜厚度. 大学物理实验. 2024(01): 31-36 .
![]() | |
2. |
易进,张瑞,薛鹏,卜韩,王志斌,李孟委. 基于弹光调制的椭偏测量驱动电路系统设计. 电子设计工程. 2024(04): 32-36+42 .
![]() | |
3. |
杨楠卓,欧阳名钊,周维虎,陈晓梅. 基于光谱反射技术的梯形刻面MEMS高深宽比沟槽深度测量仿真分析. 长春理工大学学报(自然科学版). 2020(02): 48-52+114 .
![]() | |
4. |
刘学聪,苗昕扬,詹洪磊,朱明达,张善哲,赵昆. 基于激光感生电压技术的咖啡粉粒径检测. 应用光学. 2020(05): 1117-1121 .
![]() | |
5. |
肖平平,王霏,邓满兰. 基于金属包覆波导结构的纳米间隙测量研究. 激光与光电子学进展. 2020(21): 273-277 .
![]() | |
6. |
肖平平,王霏,邓满兰,胡红武. 基于LSPR的非贵金属纳米薄膜厚度的精确测量. 光电子·激光. 2019(12): 1286-1290 .
![]() |