Litcius/Paper detail

Denoising algorithm of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e69" altimg="si43.svg"><mml:mi>Φ</mml:mi></mml:math> -OTDR signal based on curvelet transform with adaptive threshold

Desheng Li, Hao Wang, Xuewei Wang, Xiang Li, Tianye Huang, Ming‐Feng Ge, Jie Yin, Shaoxiang Chen, Huang Bao, Kai Guan, Chongwen He, Huixuan Hu, Kang Li, Zhenggang Lian

2023Optics Communications12 citationsDOIOpen Access PDF

Abstract

In this paper, a denoising scheme based on curvelet transform is proposed to improve the signal-to-noise ratio (SNR) for vibration sensing in phase-sensitive optical time-domain reflectometry (Φ-OTDR) systems. The noise level can be estimated based on non-vibration images, which can be used to set the threshold for curvelet coefficients. We further optimize the threshold according to the amplitude distribution of the curvelet coefficients. In the experimental demonstration, when the optical pulse width is 100 ns, the SNR of location information of the 100 Hz vibration events can be increased by 6.93 dB, which proves the effectiveness of the proposed method.

Topics & Concepts

CurveletReflectometryAlgorithmNoise (video)Computer scienceSIGNAL (programming language)AmplitudeOpticsArtificial intelligencePhysicsTime domainComputer visionWaveletImage (mathematics)Programming languageWavelet transformAdvanced Fiber Optic SensorsOptical Coherence Tomography ApplicationsPhotoacoustic and Ultrasonic Imaging