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Frontiers of Optoelectronics

ISSN 2095-2759

ISSN 2095-2767(Online)

CN 10-1029/TN

Postal Subscription Code 80-976

Front. Optoelectron.    2010, Vol. 3 Issue (2) : 169-178    https://doi.org/10.1007/s12200-010-0012-1
Research articles
Underwater image restoration by means of blind deconvolution approach
Fan FAN,Kecheng YANG,Min XIA,Wei LI,Bo FU,Wei ZHANG,
Wuhan National Laboratory for Optoelectronics, College of Optoelectronic Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China;
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Abstract Although the use of blind deconvolution of image restoration is a widely known concept, little literatures have discussed in detail its application in the problem of restoration of underwater range-gated laser images. With the knowledge of the point spread function (PSF) and modulation transfer function (MTF) of water, underwater images can be better restored or enhanced. We first review image degradation process and Wells’ small angle approximation theory, and then provide an image enhancement method for our underwater laser imaging system by blind deconvolution method based on small angle approximation. We also introduce a modified normalized mean square error (NMSE) method to validate the convergence of the blind deconvolution algorithm which is applied in our approach. The results of different initial guess of blind deconvolution are compared and discussed. Moreover, restoration results are obtained and discussed by intentionally changing the MTF parameters and using non-model-based PSF as the initial guess.
Issue Date: 05 June 2010
 Cite this article:   
Fan FAN,Kecheng YANG,Min XIA, et al. Underwater image restoration by means of blind deconvolution approach[J]. Front. Optoelectron., 2010, 3(2): 169-178.
 URL:  
https://academic.hep.com.cn/foe/EN/10.1007/s12200-010-0012-1
https://academic.hep.com.cn/foe/EN/Y2010/V3/I2/169
Hou W, Lee Z, Weidemann A D. Why does the secchi diskdisappear? An imaging perspective. Optics Express, 2007, 15(6): 2791–2802

doi: 10.1364/OE.15.002791
Hou W, Gray D J, Weidemann A D, Fournier G R, Forand J L. Automated underwater image restoration and retrieval of related opticalproperties. In: Proceedings of IEEE InternationalGeoscience and Remote Sensing Symposium. 2007, 1889–1892
Wells W H. Theory of small angle scattering. AGARD Lecture Series, 1973, 61
Hou W, Gray D J, Weidemann A D, Arnone R A. Comparison and validation of point spread models forimaging in natural waters. Optics Express, 2008, 16(13): 9958–9965

doi: 10.1364/OE.16.009958
Moran S E, Ulich B L, Elkins W P, Strittmatter R J, DeWeert M J. Intensified CCD (ICCD) dynamicrange and noise performance. Proceedings of SPIE, 1997, 3173: 430–457

doi: 10.1117/12.294535
Lane R G. Blind deconvolution of speckle images. Journal of the Optical Society of America A, 1992, 9(9): 1508–1514

doi: 10.1364/JOSAA.9.001508
Richardson W H. Bayesian-based iterative method of image restoration. Journal of the Optical Society of America, 1972, 62(1): 55–59

doi: 10.1364/JOSA.62.000055
Lucy L B. An iterative technique for the rectification of observeddistributions. The Astronomical Journal, 1974, 79(6): 745–754

doi: 10.1086/111605
Fish D A, Brinicombe A M, Pike E R, Walker J G. Blind deconvolution by means of the Richardson-Lucy algorithm. Journal of the Optical Society of America A, 1995, 12(1): 58–65

doi: 10.1364/JOSAA.12.000058
Gonzalez R C, Woods R E. Digital Image Processing. New Jersey: Prentice Hall, 2002
Pratt W K. Digital Image Processing: PIKS Scientific Inside. 4th ed. New Jersey: Wiley-Interscience, 2007
Zhang J, Zhang Q, He G. Blind deconvolution: multiplicative iterative algorithm. Optics Letters, 2008, 33(1): 25–27

doi: 10.1364/OL.33.000025
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