Paper
14 March 2000 Mechanisms for the conversion of hyperspectral images to chemical images
Christopher W. Brown, Dongsheng Bu, Nancy P. Camacho, Richard Mendelsohn
Author Affiliations +
Abstract
We have evaluated and combined the features of three different methods to develop an algorithm for rapidly processing hyperspectral images. The hyperspectra were initially processed with Principal Component Analysis to find the appropriate number of independent components and abstract spectral representations (loadings). Key Set Factor Analysis and SIMPLISMA (SIMPle-to-use Interactive Self- modeling Mixture Analysis) methods were combined to find `pure' wavelengths for the components from the loadings. These `pure' wavelengths were used to product initial guesses for the relative concentrations of the components, and these concentrations were used to predict the pure component spectra. The spectra were further refined by using the method of Alternating Least Squares. The methodology is demonstrated on infrared spectra of a simple, three- component chemical mixture and on a hyperspectral infrared image of cartilage tissue.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Christopher W. Brown, Dongsheng Bu, Nancy P. Camacho, and Richard Mendelsohn "Mechanisms for the conversion of hyperspectral images to chemical images", Proc. SPIE 3920, Spectral Imaging: Instrumentation, Applications, and Analysis, (14 March 2000); https://doi.org/10.1117/12.379590
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Cited by 3 scholarly publications.
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KEYWORDS
Hyperspectral imaging

Principal component analysis

Infrared radiation

Infrared imaging

Collagen

Image processing

Algorithm development

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