激光与光电子学进展, 2018, 55 (7): 070607, 网络出版: 2018-07-20   

Kuwahara滤波在布里渊光时域分析传感图像去噪中的应用 下载: 740次

Application of Kuwahara Filter in Brillouin Optical Time-Domain Analysis Sensing Image Denoising
作者单位
中国矿业大学环境与测绘学院, 江苏 徐州 221116
摘要
针对布里渊光时域分析(BOTDA)传感图像中信息在空域的相似性,利用Kuwahara滤波对传感图像去噪,根据滤波窗口内相邻像素之间的相关性恢复中心元素值。研究结果表明,Kuwahara滤波的窗口长度设置应小于并接近理论空间分辨率。利用该方法对不同信噪比的BOTDA传感图像进行去噪处理,信噪比平均提高6.7 dB,布里渊频移误差平均减小0.58 MHz,空间分辨率保持不变。该方法在不增加BOTDA传感器硬件设备的情况下提高了传感器性能,可用于高分辨率、中长距离传感数据的处理,同时也可用于其他类型的分布式光纤传感系统。
Abstract
According to the similarity of information in Brillouin optical time-domain analysis (BOTDA) sensing image in spatial domain, Kuwahara filtering method for sensing image denoising is proposed. The central element value can be restored according to the correlation among adjacent pixels in filtering window. The results show that the window size of Kuwahara filter should approach to the theoretical value of spatial resolution. The proposed method can make an average signal noise ratio (SNR) improvement of 6.7 dB and Brillouin frequency shift (BFS) error decrease of 0.58 MHz for BOTDA sensing images in different SNRs, without distorting spatial resolution. The method improves the performance of the sensor without increasing the BOTDA sensor hardware, so it has the potential application to high-resolution, long distance sensing and the other types of distributed optical fiber sensors.
参考文献

[1] Barnoski M K, Rourke M D, Jensen S M, et al. Optical time domain reflectometer[J]. Applied Optics, 1977, 16(9): 2375-2379.

[2] Froggatt M, Moore J. High-spatial-resolution distributed strain measurement in optical fiber with Rayleigh scatter[J]. Applied Optics, 1998, 37(10): 1735-1740.

[3] Farahani M A, Gogolla T. Spontaneous Raman scattering in optical fibers with modulated probe light for distributed temperature Raman remote sensing[J]. Journal of Lightwave Technology, 1999, 17(8): 1379-1391.

[4] Dakin J P, Pratt D J, Bibby G W, et al. Distributed optical fibre Raman temperature sensor using a semiconductor light source and detector[J]. Electronics Letters, 1985, 21(13): 569-570.

[5] Horiguchi T, Shimizu K, Kurashima T, et al. Development of a distributed sensing technique using Brillouin scattering[J]. Journal of Lightwave Technology, 1995, 13(7): 1296-1302.

[6] Kurashima T, Horiguchi T, Tateda M. Distributed-temperature sensing using stimulated Brillouin scattering in optical silica fibers[J]. Optics Letters, 1990, 15(18): 1038-1040.

[7] Horiguchi T, Kurashima T, Tateda M. Tensile strain dependence of Brillouin frequency shift in silica optical fibers[J]. IEEE Photonics Technology Letters, 1989, 1(5): 107-108.

[8] Lopez-Higuera J M, Rodriguez C L, Quintela I A, et al. Fiber optic sensors in structural health monitoring[J]. Journal of Lightwave Technology, 2011, 29(4): 587-608.

[9] Bao X, Chen L. Recent progress in Brillouin scattering based fiber sensors[J]. Sensors, 2011, 11(4): 4152-4187.

[10] Alahbabi M N, Cho Y T, Newson T P. 150-km-range distributed temperature sensor based on coherent detection of spontaneous Brillouin backscatter and in-line Raman amplification[J]. Journal of the Optical Society of America B, 2005, 22(6): 1321-1324.

[11] Voskoboinik A, Zhang Z Y, Almaiman A, et al. Differential pulse-width pair BOTDA using simultaneous frequency domain interrogation[C]∥Conference on Lasers and Electro-Optics: Science and Innovations. San Jose, California United States, 2013, CTh4H: CTh4H.5.

[12] Soto M A, Taki M, Bolognini G, et al. Optimization of a DPP-BOTDA sensor with 25 cm spatial resolution over 60 km standard single-mode fiber using Simplex codes and optical pre-amplification[J]. Optics Express, 2012, 20(7): 6860-6869.

[13] Kishida K, Li C H, Nishiguchi K. Pulse pre-pump method for cm-order spatial resolution of BOTDA[J]. Proceedings of SPIE, 2005, 5855: 559-562.

[14] Brown A W, Colpitts B G, Brown K. Distributed sensor based on dark-pulse Brillouin scattering[J]. IEEE Photonics Technology Letters, 2005, 17(7): 1501-1503.

[15] Soto M A, Ramírez J A, Thévenaz L. Intensifying the response of distributed optical fibre sensors using 2D and 3D image restoration[J]. Nature Communications, 2016, 7: 10870.

[16] He H, Shao L, Li H, et al. SNR enhancement in phase-sensitive OTDR with adaptive 2-D bilateral filtering algorithm[J]. IEEE Photonics Journal, 2017, 9(3): 1-10.

[17] Soto G, Fontbona J, Cortez R, et al. An online two-stage adaptive algorithm for strain profile estimation from noisy and abruptly changing BOTDR data and application to underground mines[J]. Measurement, 2016, 92: 340-351.

[18] 严哲, 顾汉明, 蔡成国. 基于各向异性扩散滤波的地震图像增强处理[J]. 石油地球物理勘探, 2013, 48(3): 390-394.

    Yan Z, Gu H M, Cai C G. Seismic image enhancement based on anisotropic diffusion[J]. Oil Geophysical Prospecting, 2013, 48(3): 390-394.

[19] 李光明, 冯磊. 基于图像信息的地震断层增强方法及其应用[J]. 地球物理学进展, 2012, 27(5): 2138-2143.

    Li G M, Feng L. Image processing the enhancement of the seismic fault of method and its application[J]. Progress in Geophysics, 2012, 27(5): 2138-2143.

[20] Bartyzel K. Adaptive Kuwahara filter[J]. Signal, Image and Video Processing, 2016, 10(4): 663-670.

[21] Agrawal G P. Nonlinear fiber optics[M]. 3rd Ed. San Diego: Academic Press, 2001: 195-211.

[22] Soto M A, Ramírez J A, Thévenaz L. Intensifying Brillouin distributed fibre sensors using image processing[J]. Proceedings of SPIE, 2015, 9634: 96342D.

[23] Azad A K,Khan F N, Alarashi W H, et al. Temperature extraction in Brillouin optical time-domain analysis sensors using principal component analysis based pattern recognition[J]. Optics Express, 2017, 25(14): 16534-16549.

[24] 张燕君, 徐金睿, 付兴虎. 基于GA-QPSO混合算法的Brillouin散射谱特征提取方法[J]. 中国激光, 2016, 43(2): 0205002.

    Zhang Y J, Xu J R, Fu X H. Method of Brillouin scattering spectrum character extraction based on genetic algorithm and quantum-behaved particle swarm optimization hybrid algorithm[J]. Chinese Journal of Lasers, 2016, 43(2): 0205002.

[25] 刘银, 付广伟, 张燕君, 等. 基于径向基函数神经网络的传感布里渊散射谱特征提取[J]. 光学学报, 2012, 32(2): 0206002.

    Liu Y, Fu G W, Zhang Y J, et al. A novel method for Brillouin scattering spectrum of distributed sensing systems based on radial basis function neural networks to extract features[J]. Acta Optica Sinica, 2012, 32(2): 0206002.

[26] 尚秋峰, 胡雨婷, 刘薇. 基于互相关卷积与高阶矩质心计算的布里渊散射谱特征提取[J]. 中国激光, 2017, 44 (11): 1106011.

    Shang Q F, Hu Y T, Liu W. Feature extraction of Brillouin scattering spectrum based on cross-correlation convolution and high-order centroid calculation[J]. Chinese Journal of Lasers, 2017, 44(11): 1106011

[27] Buades A, Coll B, Morel J M.A review of image denoising algorithms, with a new one[J]. Multiscale Modeling & Simulation, 2005, 4(2): 490-530.

[28] Papari G, Petkov N, Campisi P. Artistic edge and corner enhancing smoothing[J]. IEEE Transactions on Image Processing, 2007, 16(10): 2449-2462.

孟彦杰, 查剑锋. Kuwahara滤波在布里渊光时域分析传感图像去噪中的应用[J]. 激光与光电子学进展, 2018, 55(7): 070607. Meng Yanjie, Zha Jianfeng. Application of Kuwahara Filter in Brillouin Optical Time-Domain Analysis Sensing Image Denoising[J]. Laser & Optoelectronics Progress, 2018, 55(7): 070607.

本文已被 2 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!