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Gamut Compression and Extension Algorithms Based on Observer Experimental Data
Author(s) -
Kang ByoungHo,
Morovic Ján,
Luo M. Ronnier,
Cho MaengSub
Publication year - 2003
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.03.0102.3315
Subject(s) - gamut , observer (physics) , computer vision , artificial intelligence , computer science , extension (predicate logic) , color space , data compression , pixel , image compression , algorithm , image (mathematics) , image processing , physics , quantum mechanics , programming language
Gamut compression algorithms have traditionally been defined functionally and then tested with deductive methods, e.g., psychophysical experiments. Our study offers an alternative, an inductive method, in which observers judge image colors to represent the original images more accurately. We developed a computer‐controlled interactive tool that modifies the color appearance of pictorial images displayed on a monitor. In experiments, observers used the tool to alter color pixels according to the region of color space to which they belonged. We created three different gamut compression algorithms based on the observer experimental data. Observer groups evaluated the performance of the newly‐developed algorithms, existing gamut compression algorithms, and an image based on the average observers’ results from experiments in this study. The study of gamut extension is unlike the study of gamut compression in that it mainly deals with the degree of image pleasantness as judged by observers. The results of the gamut extension experiments in this study not only make available worthwhile data but also suggest a methodology for using the observer experimental tool for future gamut extension research.

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