Wavelet:  A New Trend in Chemistry

Abstract

Since 1989, wavelet transform (WT) has attracted much interest of chemists working on signal and image processing, and the WT-based techniques have been successfully applied to the chemical signal processing. This approach has been demonstrated as fast in computation with localization and having quick decay properties, in contrast to the popular methods existing, especially to the fast Fourier transform. More than 370 papers have been published up to the year 2002 which covered applications of WT in various fields of chemistry, including analytical chemistry, chemical physics, and quantum chemistry. In this paper, we report on applications of WT to data compression, data smoothing and denoising, baseline and background correction, resolution of multicomponent overlapping signals, regression and classification, and analytical images processing in analytical chemistry. Through this report we wish to induce greater interest of chemists in WT and to obtain greater benefits from using the WT-based techniques.

Structural and Characteristics Change of Water Hyacinth Fiber due to Combine Effect of Plasma and Nano-technology

“…WT analysis can provide multi-scale morphological picture related to any frequency data [21,22,23]. It normally provides verifiable capacity of non-stationary signals [24].…”

“…Wavelet transformation can help us to meet information on surface morphology and topography [21], which is considered in localized space and frequency. Using the algorithm multi-resolution signal decomposition (MRSD), WT can extend the image information directly at different resolution for enabling interpretation of the image details from a lower-to-higher resolution [22].…”

Wavelet-based classification and influence matrix analysis method for the fast discrimination of Chinese herbal medicines according to the geographical origins with near infrared spectroscopy

“…WT has been proven to be a powerful tool for dimension reduction and noise removal. 14 Vannucci et al 15 have used wavelet-based feature selection technique to classify the NIR and mass spectra. In combination with WT, a lot of algorithms, such as wavelet transformation-uninformative variable elimination (WT-UVE), 16 wavelet transformation-modi¯ed uninformative variable elimination (WT-MUVE), 17 wavelet orthogonal signal correction (WOSC), 10 wavelet packet transform for e±cient pattern recognition of signals (WPTER), 18 etc., have also been proposed and successfully used for NIR calibration and classi¯cation.…”

Simultaneous Spectrophotometric Determination of Metformin Hydrochloride and Glibenclamide in Binary Mixtures Using Combined Discrete and Continuous Wavelet Transforms

“…13,14 Wavelet transform is a strong tool for signal de-noising 15 and baseline removal, 16 signal compression and processing, and multicomponent analysis; it has been established as a powerful technique in analytical chemistry. [17][18][19][20] By means of wavelet transform, an original signal can be decomposed into localized contributions characterized by a scale parameter. Each contribution represents a portion of the signal with a different frequency.…”