Characteristic Peak Extraction Method for Ultraviolet Raman Spectroscopy with Low Signal-to-Noise Ratio

Abstract

The invention discloses a method for extracting characteristic peaks of ultraviolet Raman spectra with low signal-to-noise ratio, belonging to the field of spectrum detection and spectrum processing technology and signal processing. The invention collects ultraviolet Raman signals in real time, performs statistics on collected Raman signal data, and predicts the effective peak value of Raman signals. Each frame of Raman spectrum collected is processed, and for each frame of Raman spectrum, each frame of Raman spectrum is divided into various regions through the obtained effective trough, and the properties of each segmented region are judged separately . For each noise region, let each point be equal to the minimum value of the region, and then merge the Raman signal region and the processed noise region. Afterwards, the processed N+1 frame spectra are spliced ​​into a 2D image along the time axis, and the 2D image is filtered through an iterative bilateral filtering method. After filtering, the N+1 spectra are superimposed and normalized along the time axis. Obtain clean Raman characteristic peak spectral images.

Description

technical field [0001] The invention relates to a method for extracting characteristic peaks of ultraviolet Raman spectra with low signal-to-noise ratio, in particular to a method for obtaining clean and effective Raman characteristic peak images for real-time low signal-to-noise ratio ultraviolet Raman signals, which belongs to the spectrum Detection and spectral processing techniques as well as the field of signal processing. Background technique [0002] Raman spectroscopy is a non-destructive spectroscopic detection method based on inelastic light scattering (i.e., changes in the energy / frequency of the incident laser light) from laser-matter interactions. By measuring the specific Raman spectrum (Raman fingerprint) of the molecular system to be tested, the sample can be quickly, simply, and repeatably non-contact non-destructive testing and quantitative analysis, with short time required, small amount of sample, and accurate measurement results Features. However, the ...

AI Technical Summary

Problems solved by technology

However, the sensitivity of Raman spectroscopy detection is low (the intensity of Rayleigh scattered rays is only 10 of the incident light intensity. -3 , the Raman spectrum intensity is only about 10 of the Rayleigh line -3 ), especially for some small, portable or simple ultraviolet Raman spectroscopy detection systems, due to factors such as low laser power, insufficient laser stability, and too much noise of the uncooled CCD, the noise of the detection results is greatly affected, and the Raman signal signal Low noise ratio, difficult to identify Raman characteristic peaks

[0003] Some traditional signal processing methods can remove some random noise, so that the Raman characteristic peaks are prominent, but it is not necessarily ideal for Raman spectroscopy, because many weak Raman peaks, whether in terms of amplitude or waveform, close to noise

Therefore, in the process of removing random noise, many weak Raman effective signals will be lost, and the signal-to-noise ratio has not improved much

Images