Optical detection algorithm for seafloor roughness and its experimental study

GAO Sunpei; XU Jian; ZOU Bo

doi:10.5768/JAO201940.0302005

Volume 40 Issue 3

May 2019

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GAO Sunpei, XU Jian, ZOU Bo. Optical detection algorithm for seafloor roughness and its experimental study[J]. Journal of Applied Optics, 2019, 40(3): 435-439. doi: 10.5768/JAO201940.0302005

Citation:

GAO Sunpei, XU Jian, ZOU Bo. Optical detection algorithm for seafloor roughness and its experimental study[J]. Journal of Applied Optics, 2019, 40(3): 435-439. doi: 10.5768/JAO201940.0302005

GAO Sunpei, XU Jian, ZOU Bo. Optical detection algorithm for seafloor roughness and its experimental study[J]. Journal of Applied Optics, 2019, 40(3): 435-439. doi: 10.5768/JAO201940.0302005

Citation:

GAO Sunpei, XU Jian, ZOU Bo. Optical detection algorithm for seafloor roughness and its experimental study[J]. Journal of Applied Optics, 2019, 40(3): 435-439. doi: 10.5768/JAO201940.0302005

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Optical detection algorithm for seafloor roughness and its experimental study

doi: 10.5768/JAO201940.0302005

School of Marine Science and Technology, Tianjin University, Tianjin 300072, China

Received Date: 2018-09-26
Rev Recd Date: 2019-01-19
Publish Date: 2019-05-01

Abstract

Abstract

As an important physical property of seafloor sediments, the seafloor micro-topography roughness is of great significance to marine engineering and scientific investigation. How to measure seafloor micro-topography roughness by optical method has been a hot topic in this field in recent years. Based on the shape from shading (SFS) algorithm in optics, a fast seafloor micro-topography roughness algorithm was put forward. While constructing the model, the absorption and attenuation model of underwater light propagation was considered, and the seafloor micro-topography roughness was measured and the parameters were fitted according to the power law form. Simulation results prove that the algorithm has 95% confidence, it is suitable for seafloor micro-topography roughness measurement, and its validity and correctness are proved by experiments.
- marine technology,
- seafloor acoustic scattering,
- shape from shading,
- measurement of seafloor micro-topography roughness

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References(15)

References

唐应吾.海底沉积物上的声反射[J].声学学报, 1994, 19(4):278-289. http://www.cnki.com.cn/Article/CJFDTotal-XIBA404.004.htm

TANG Yingwu. Reflection of acoustic waves from marine sediment[J]. Acta Acustica, 1994, 19(4):278-289. http://www.cnki.com.cn/Article/CJFDTotal-XIBA404.004.htm

LYONS A P, POULIQUEN E. Advances in high-resolution seafloor characterization in support of high-frequency underwater acoustics studies:techniques and examples[J]. Measurement Science and Technology, 2004, 15(12):R59-R72. http://cn.bing.com/academic/profile?id=5a83258670581ec5ac3afc83d6ba1414&encoded=0&v=paper_preview&mkt=zh-cn

SCHMIDT V E, RZHANOV Y. Measurement of micro-bathymetry with a GOPRO underwater stereo camera pair[C]. USA: IEEE, 2012: 1-6.

CHOTIROS N P, ISAKSON M J, PIPER J N, et al. Sea floor roughness measured by a laser profiler on a ROV[C].USA: IEEE, 2014: 1-4.

DI MARTINO G, DI SIMONE A, IODICE A, et al. On shape from shading and SAR images: an overview and a new perspective: 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, July 13-18, 2014, Canada[C].USA: IEEE, 2014: 1333-1336.

CLAY C S, LEONG W K. Acoustic estimates of the topography and roughness spectrum of the sea floor southwest of iberian peninsula[M].Boston: Springer, 1974: 373-446.

陈刚, 周文静, 胡祯, 等.表面粗糙度数字全息检测[J].应用光学, 2014, 35(6):1040-1047. http://www.yygx.net/CN/abstract/abstract10530.shtml

CHEN Gang, ZHOU Wenjing, HU Zhen, et al. Surface roughness measurement based on digital holography[J]. Journal of Applied Optics, 2014, 35(6):1040-1047. http://www.yygx.net/CN/abstract/abstract10530.shtml

陈曼龙, 侯东明, 王会江.车削零件表面粗糙度图像法检测优选方法[J].应用光学, 2017, 38(2):227-230. http://www.yygx.net/CN/abstract/abstract10921.shtml

CHEN Manlong, HOU Dongming, WANG Huijiang. Optimal method for image detection based on surface roughness of turning parts[J]. Journal of Applied Optics, 2017, 38(2):227-230. http://www.yygx.net/CN/abstract/abstract10921.shtml

HLéN J, BENGTSSON E, LINDELL T. Color correction of underwater images based on estimation of diffuse attenuation coefficients: The PICS Conference, An International Technical Conference on The Science and Systems of Digital Photography, including the Fifth International Symposium on Multispectral Color Science, NY, May 13, 2003[C].[S.l.]: [s.n.], 2003: 325-329.

ZHANG S M, NEGAHDARIPOUR S. 3-D shape recovery of planar and curved surfaces from shading cues in underwater images[J]. IEEE Journal of Oceanic Engineering, 2002, 27(1):100-116. doi: 10.1109/48.989895

YU T, XU N, AHUJA N. Recovering shape and reflectance model of non-lambertian objects from multiple views[J]. IEEE Cvpr, 2004, 2:226-233. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=CC026945001

ZHENG Q, CHELLAPPA R. Estimation of illuminant direction, albedo, and shape from shading[C]//Proceedings of 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA: IEEE, 1991: 540-545.

TSAI P S, SHAH M. A fast linear shape from shading[C]//Proceedings of 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. USA: IEEE, 1992: 734-736.

BRIGGS K B, LYONS A P, POULIQUEN E, et al. Seafloor Roughness, Sediment Grain Size, and Temporal Stability[C]//Underwater Acoustic Measurements: Technologies &Results. USA: AGRIS, 2005.

BRIGGS K B. Microtopographical roughness of shallow-water continental shelves[J]. IEEE Journal of Oceanic Engineering, 1989, 14(4):360-367. doi: 10.1109/48.35986

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