Noise reduction for improving the performance of gas detection algorithms in the FTIR spectrometer

Hyeong-Geun Yu; Jae-Hoon Lee; Dong-Jo Park; Hyun-Woo Nam; Byeong-Hwang Park

doi:10.1117/12.2304629

8 May 2018 Noise reduction for improving the performance of gas detection algorithms in the FTIR spectrometer

Hyeong-Geun Yu, Jae-Hoon Lee, Dong-Jo Park, Hyun-Woo Nam, Byeong-Hwang Park

Proceedings Volume 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV; 106441Q (2018) https://doi.org/10.1117/12.2304629
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

A passive Fourier transform infrared (FTIR) spectrometer is an instrument that can detect and identify chemical contaminants. An FTIR spectrometer exploits the infrared radiation of the surrounding terrain as a light source and receives a mixed signal of background signal, gas signal, and noise. The performance of most detection algorithms for detecting gaseous plumes, such as the normalized matched filter (NMF) and adaptive subspace detector (ASD), deteriorates due to the noise generated by an FTIR spectrometer. In this paper, a noise reduction algorithm based on the maximum noise fraction (MNF) transform to improve the performance of hazardous gas detection algorithms is proposed. We apply the MNF transform to the measured spectra and remove the high noise fraction component. Then the noise-reduced spectra are restored by conducting the inverse MNF transform. The experimental results show that the proposed algorithm reduces the noise and enhances the gas detection performance.

Citation Download Citation

Hyeong-Geun Yu, Jae-Hoon Lee, Dong-Jo Park, Hyun-Woo Nam, and Byeong-Hwang Park "Noise reduction for improving the performance of gas detection algorithms in the FTIR spectrometer", Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 106441Q (8 May 2018); https://doi.org/10.1117/12.2304629

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