希尔伯特-黄变换
噪音(视频)
降噪
算法
信号(编程语言)
噪声测量
计算机科学
信噪比(成像)
人工智能
模式识别(心理学)
计算机视觉
图像(数学)
电信
滤波器(信号处理)
程序设计语言
作者
Liang Pan,Kun Liu,Junfeng Jiang,Chunyu Ma,Tian Miao,Tiegen Liu
标识
DOI:10.1109/jsen.2016.2623860
摘要
A de-noising algorithm based on ensemble empirical mode decomposition (EEMD) method is employed in this paper for Raman-based distributed temperature sensor (RDTS). We first decompose the noisy signal using the EEMD and find local maxima on each intrinsic mode function (IMF) whose zero contour line is used to determine noise interval. The signal is then de-noised and reconstructed by removing the noise components of each IMF. The experimental results demonstrated that the proposed de-noising algorithm can enhance the signal-to-noise ratio by 8.8 dB while maintaining spatial resolution. The temperature error reduction of 3.2 °C can be achieved at 10 km using conventional RDTS without losing any detail.
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