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Volume: 3 | Article ID: art00093
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Learning Techniques in Imaging System Design and Spectral Image Processing
Vladimir Bochko
Yoichi Miyake
Jussi Parkkinen
  DOI :  10.2352/CGIV.2006.3.1.art00093  Published Online :  January 2006
Abstract

Many kinds of color imaging systems have been developed and equipped with an image processing technique. Most accurate imaging systems are implemented if spectral systems and spectral image processing are utilized. In this paper, the machine learning techniques in spectral images that extend traditional image processing methods are considered. Advantages and drawbacks of learning methods in various applications are described and discussed.

Journal Title : Conference on Colour in Graphics, Imaging, and Vision
Publisher Name : Society of Imaging Science and Technology
Publisher Location : 7003 Kilworth Lane, Springfield, VA 22151, USA
Subject Areas :
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 DOI 10.2352/CGIV.2006.3.1.art00093
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Vladimir Bochko, Yoichi Miyake, Jussi Parkkinen, "Learning Techniques in Imaging System Design and Spectral Image Processing"  in Proc. IS&T CGIV 2006 3rd European Conf. on Colour in Graphics, Imaging, and Vision,  2006,  pp 452 - 457,  https://doi.org/10.2352/CGIV.2006.3.1.art00093

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  Copyright statement 
Copyright © Society for Imaging Science and Technology 2006
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2158-6330(20060101)2006:1L.452;1-
cgiv_v2006n1/splitsection93.xml
/ist/cgiv/2006/00002006/00000001/art00093
Articles
Learning Techniques in Imaging System Design and Spectral Image Processing
BochkoVladimir
MiyakeYoichi
ParkkinenJussi
01012006
2006
1
452
457
2006
Many kinds of color imaging systems have been developed and equipped with an image processing technique. Most accurate imaging systems are implemented if spectral systems and spectral image processing are utilized. In this paper, the machine learning techniques in spectral images that extend traditional image processing methods are considered. Advantages and drawbacks of learning methods in various applications are described and discussed.