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Volume: 8 | Article ID: art00049
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Gamut Compression Algorithm Development on the basis of Observer Experimental Data
Byoung-Ho Kang
Maeng-Sub Cho
Ján Morovic
M. Ronnier Luo
  DOI :  10.2352/CIC.2000.8.1.art00049  Published Online :  January 2000
Abstract

An interactive tool was developed for matching a pair of pictorial images having different colour gamuts. Three GCAs (Gamut Compression Algorithms) were developed based on the experimental data from a panel of 22 observers. Further experiments were conducted to evaluate the performance between the newly-developed and six existing GCAs together with an image based on the average observers' results. One of the new algorithms significantly outperformed the others. A generally usable algorithm was also developed for taking into account all possible application conditions.

Journal Title : Color and Imaging Conference
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/CIC.2000.8.1.art00049
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  Cite this article 

Byoung-Ho Kang, Maeng-Sub Cho, Ján Morovic, M. Ronnier Luo, "Gamut Compression Algorithm Development on the basis of Observer Experimental Data"  in Proc. IS&T 8th Color and Imaging Conf.,  2000,  pp 268 - 272,  https://doi.org/10.2352/CIC.2000.8.1.art00049

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Copyright © Society for Imaging Science and Technology 2000
72010350
Color and Imaging Conference
color imaging conf
2166-9635
Society of Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151, USA
2166-9635(20000101)2000:1L.268;1-
cic_v2000n1/splitsection49.xml
/ist/cic/2000/00002000/00000001/art00049
Articles
Gamut Compression Algorithm Development on the basis of Observer Experimental Data
KangByoung-Ho
ChoMaeng-Sub
MorovicJán
LuoM. Ronnier
01012000
2000
1
268
272
2000
An interactive tool was developed for matching a pair of pictorial images having different colour gamuts. Three GCAs (Gamut Compression Algorithms) were developed based on the experimental data from a panel of 22 observers. Further experiments were conducted to evaluate the performance between the newly-developed and six existing GCAs together with an image based on the average observers' results. One of the new algorithms significantly outperformed the others. A generally usable algorithm was also developed for taking into account all possible application conditions.