Objective and efficient terahertz signal denoising by transfer function reconstruction

Xuequan Chen,Qiushuo Sun,Rayko I Stantchev,Emma Pickwell-Macpherson

doi:10.1063/5.0002968

Abstract

As an essential processing step in many disciplines, signal denoising efficiently improves data quality without extra cost. However, it is relatively under-utilized for terahertz spectroscopy. The major technique reported uses wavelet denoising in the time-domain, which has a fuzzy physical meaning and limited performance in low-frequency and water-vapor regions. Here, we work from a new perspective by reconstructing the transfer function to remove noise-induced oscillations. The method is fully objective without a need for defining a threshold. Both reflection imaging and transmission imaging were conducted. The experimental results show that both low- and high-frequency noise and the water-vapor influence were efficiently removed. The spectrum accuracy was also improved, and the image contrast was significantly enhanced. The signal-to-noise ratio of the leaf image was increased up to 10 dB, with the 6 dB bandwidth being extended by over 0.5 THz.

Highlights

Spectroscopy at terahertz (THz) frequencies has been extensively studied in the last three decades since the invention of THz time-domain spectroscopy (TDS)
Noiseinduced oscillations on the characterized sample properties were efficiently removed. This limits its versatility as it is not applicable when the sample properties are not extracted in a measurement. Another technique of autoregressive extrapolation reported by Dong et al extends the effective bandwidth by predicting values of the transfer function from a high-signal-tonoise ratio (SNR) region
The 0 dB SNR indicates no useful information was provided. This is decided by the denoising principle as even if Msmooth has deviated from Mtheory far outside of the effective bandwidth, the reconstructed signal is not affected as the amplitudes in this region are extremely small

Summary

INTRODUCTION

Spectroscopy at terahertz (THz) frequencies has been extensively studied in the last three decades since the invention of THz time-domain spectroscopy (TDS). Fourier filtering usually applies a low-pass or band-pass filter to remove noise outside the effective bandwidth.15 It improves the time-domain signal quality but has no improvement to the useful spectrum at all. Unlike Fourier coefficients, which stand for the physical properties of an electromagnetic wave, the processing of the wavelet coefficients is mainly numerically based with little physical meaning It has a limited performance at low frequencies and in the regions with dense water-vapor absorptions. This limits its versatility as it is not applicable when the sample properties are not extracted in a measurement Another technique of autoregressive extrapolation reported by Dong et al extends the effective bandwidth by predicting values of the transfer function from a high-SNR region.. A fresh leaf was scanned by transmission to demonstrate the improvement in the image quality and the effective bandwidth

METHOD

Output the top ranked Mi in the last iteration

EXPERIMENTS

Leaf transmission imaging

Findings

DISCUSSION