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Multispectral technology applications

Date Published: 26th April 2005
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Author: Dr.Mohamed Selim El Kayyali RSS Views: N/A PRINT ASK ABOUT THIS ARTICLE
Human eyes receive colors in three-dimensional space, owning the presence of three types of color receptors. Early psychophysical research demonstrated conclusively that three component values are sufficient to represent any perceived color, and these values can be quantified using the CIE XYZ tristimulus.

The interaction between illumination and materials cannot be accurately simulated with three samples. Researchers found that spectral prefiltering to minimize colors error in scenes with single dominant illuminant spectrum, regardless of he rendering color space.

In multispectral images, the same spatial region is captured multiple times using different imaging modalities. These modalities usually consist of measurements at different optical wavelengths, medical multispectral as example, may combine MRI, CT and X-ray images in single data set for one multiplayer, and as known that multispectral theory are three dimensional data sets, where the third layer (spectral) is often qualitatively different from the other two.


The most common multispectral images are those RGB images, which contain three spectral image planes, which all lie in the visible range of the optical band. Another example for multispectral images, those that use CMYK colors in printing, these multispectral color produce continues range of colors.

In applications such as remote sensing, multispectral images were first used the multiple images corresponding to each band in optical spectrum, more recently multispectral images have come to refer to any image formed by multiple spatially registered scalar images, independent of the specific manner in which the individual images were obtained.

In biometric applications, a new biometric sensor based on multispectral imaging technology were designed, the main approach is capture multispectral image for finger print, the multispectral technology is being developed as sensor that can be combined with standard optical finger print sensor to provide high assurance by measured finger print comes from genuine finger.



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Source: http://www.articlealley.com/article_1604_11.html
About the Author
Occupation: Researcher Professor
Dr. Kayyali, PhD & M. Sc in image processing West Coast University, Founder of Kayyali Theory for edge detection, Dr Kayyali has published many papers and technical reports in image processing, his book in digital image processing was published by University San Martin de Porres, he is IEEE, CIPPRS (Canadian Image processing Society) and BCS (British Computer Society ) member
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