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Enhanced Chemical Classification of Raman Images Using Multiresolution Wavelet Transformation

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Abstract:

Multiresolution wavelet transformation (MWT) and block thresholding is used to effectively suppress both background and noise interference while minimally distorting Raman spectral features. The performance of MWT as a spectral pre-processing algorithm is demonstrated using both synthetic spectra and experimental hyper-spectral Raman images with large background and noise components. The results are quantified by comparing correlation coefficients of synthetic spectra with either the same or different backgrounds. The improved chemical imaging performance obtained using MWT is demonstrated by comparing principal component analysis (PCA) channel images and spectral angle mapping (SAM) classified images before and after MWT pre-processing.

Keywords: BLOCK THRESHOLD; DENOISE; IMAGE CLASSIFICATION; RAMAN IMAGING; WAVELET TRANSFORM

Document Type: Research Article

DOI: http://dx.doi.org/10.1366/0003702011953289

Publication date: September 1, 2001

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