Cao, G., Zhao, Y., Ni, R.-R., Yu, L.-F. and Tian, H.-W. (2010) Forensic Detection of Median Filtering in Digital Images. 2010 IEEE International Conference on Multimedia and Expo, 19-23 July 2010, Suntec City, Singapore, 89-94.
https://doi.org/10.1109/ICME.2010.5583869

has been cited by the following article:

• TITLE: Research on Noise Reduction Approach of Raman-Based Distributed Temperature Sensor Based on Nonlinear Filter

  AUTHORS: Xiang Wang, Tong Liu, Honghui Wang

  KEYWORDS: Raman-Based Distributed Temperature Sensor, Noise Reduction, Temperature Measurement

  JOURNAL NAME: Open Journal of Applied Sciences, Vol.9 No.8, August 15, 2019

  ABSTRACT: The accuracy of temperature measurement is often reduced due to random noise in Raman-based distributed temperature sensor (RDTS). A noise reduction method based on a nonlinear filter is thus proposed in this paper. Compared with the temperature demodulation results of raw signals, the proposed method in this paper can reduce the average maximum deviation of temperature measurement results from 4.1°C to 1.2°C at 40.0°C, 50.0°C and 60.0°C. And the proposed method in this paper can improve the accuracy of temperature measurement of Raman-based distributed temperature sensor better than the commonly used wavelet transform-based method. The advantages of the proposed method in improving the accuracy of temperature measurement for Raman-based distributed temperature sensor are quantitatively reflected in the maximum deviation and root mean square error of temperature measurement results. Therefore, this paper proposes an effective and feasible method to improve the accuracy of temperature measurement results for Raman-based distributed temperature sensor.