Denoising of Spectral Signal in Miniature Spectrometer Based on Stationary Wavelet Transform

Abstract

In process of real time acquisition and transmission, the spectral signal obtained by miniature spectrometer may contain noise signals superposed on it. But the traditional denoising methods can't achieve the expected performance because of their limitations. A de-noising method for spectral signal in miniature spectrometer based on Stationary Wavelet Transform (SWT) is proposed. We compared the performance of our de-nosing method with that of the traditional method. Simulation and experimental results prove that using sym5 basis, decomposition at level 5, soft shrinkage function with heuristic SURE threshold rule achieved superior performance in miniature spectrometer spectral signal denoising.

Algorithm Research on Detail and Contrast Enhancement of High Dynamic Infrared Images

“…However, the noise is The high-frequency information layer contains the detail and contour information of the image, as well as the noise information of the image, which first needs to be denoised. In addition, the effective information should be enhanced for subsequent image applications [22][23][24]. Traditional image denoising, such as median filtering, mean filtering, etc., assume that the signal and noise are in different frequency bands.…”