应用光学, 2017, 38 (1): 42, 网络出版: 2017-02-23   

水面波动和水体湍流退化图像的复原方法

Correction methods for water fluctuation and underwater turbulence degraded imaging
作者单位
北京理工大学 光电学院 光电成像技术与系统教育部重点实验室, 北京 100081
摘要
水面波动对水下图像造成的畸变和水体湍流造成的模糊等严重制约了空中对水下目标探测、水下透空目标警戒、海上搜救等的应用, 实现畸变和湍流校正具有重要的意义。综述了复原水面波动和水体湍流引起的图像失真的研究进展, 给出了基于幸运块(lucky patch)选择的校正、基于图像配准的校正、基于水面波形估计的校正和基于图像退化模型的校正四大类方法的特点及典型的图像复原效果, 并分析了复原水面波动和水体湍流退化图像复原方法进一步深入研究的内容。
Abstract
Underwater image suffers from distortions and blurs due to water fluctuations and underwater turbulence that restricts the development of underwater surveillance, underwater target alert in the air, maritime search severely. The realization of distortion and turbulence correction has great significance. Most recent developments for the degraded image by water fluctuations and underwater turbulence are reviewed in this paper, and four methods and typical image restoration results based on lucky patch, image registration, water-waveestimation and image degradation model are summarized accordingly. Further research directions for restoring underwater degraded image are analyzed at the end of the paper.
参考文献

[1] Efros A, Isler V, Shi J, et al. Seeing through water[J]. Advances in Neural Information Processing Systems, 2005, 17: 393-400.

[2] Fried D L. Probability of getting a lucky short-exposure image through turbulence[J]. JOSA, 1978, 68(12): 1651-1657.

[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.

[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.

[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.

[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.

[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.

[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.

[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.

[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.

    Li Xiongfei, Zhang Cunli, Li Hongpeng, et al. Development of medical image registration technology[J].Computer Science, 2010,37(7): 27-33.

[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.

    Wang Wei, Su Zhixun. Medical image registration based on moving least squares[J]. Computer Science, 2010, 37(9): 270-271.

[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.

    Li Lei, Wang Qing, Xiao Zhaolin. Underwanter image restoration algorithm from distorted video[J]. Journal of System Simulation,2012, 24(1): 188-191.

[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.

    Zhang Zhiqiang. A method to perform 3D reconstruction on distorted image serie[J]. Software, 2013, 34(10): 100-105.

[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.

[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.

    Yang Bo, Zhang Wensheng, Xie Yuan. Research on distortion-free fusion of sequence images[J]. Computer Science, 2013, 40(10): 261-264.

[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.

[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.

[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.

[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.

[21] Tian Y, Narasimhan S G. Globally optimal estimation of nonrigid image distortion[J]. International Journal of Computer Vision, 2012, 98(3): 279-302.

[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.

[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.

[26] McGlamery B L. A computer model for underwater camera systems[J].SPIE Ocean Optics, 1979, 208: 221-231.

[27] Jaffe J S.Computer modeling and the design of optimal underwaterimagingsystems[J]. IEEE Journal of Oceanic Engineering, 1990, 15(2): 101-111.

[28] Trucco E,Olmos-Antillon A T. Self-tuning underwater image restoration[J]. IEEE Journal of Oceanic Engineering, 2006, 31(2): 511-519.

[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

[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.

[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.

[32] Hou W W. A simple underwater imaging model[J]. Optics Letters, 2009, 34(17): 2688-2690.

[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.

[34] Hou W, Goode W, Kanaev A. Underwater image quality degradation by scattering[C]//OCEANS, 2012-Yeosu. New York: IEEE, 2012: 1-5.

[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.

[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.

[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.

[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.

鲁啸天, 杨天鸣, 金伟其, 刘敬, 温仁杰. 水面波动和水体湍流退化图像的复原方法[J]. 应用光学, 2017, 38(1): 42. 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.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!