@Article{braquelaire-97,
author = "Braquelaire, Jean Pierre. and Luc Brun",
title = "Comparison and Optimization of Methods of Color
Image Quantization",
journal = "IEEE Transactions on Image Processing",
year = 1997,
volume = 6,
number = 7,
pages = "1048-1052",
month = "july",
url= {article(.ps.gz) :=http://www.greyc.ensicaen.fr/~luc/ARTICLES/articleIEEE.ps.gz, article(.ps) :=http://www.greyc.ensicaen.fr/~luc/ARTICLES/articleIEEE.ps.gz},
theme= {quantification},
abstract = "Color image quantization is the process of reducing
the number of colors in a digital color image has
been widely studied for the last fifteen years. In
this paper the different steps of clustering methods
are studied. The methods are compared step by step
and some optimizations of the algorithms and data
structures are given. A new color space called
$H1H2H3$ is introduced which improves quantization
heuristics. A low-cost quantization scheme is
proposed."
}
@InProceedings{braquelaire-95-1,
author = "Braquelaire, Jean Pierre and Luc Brun",
title = "Quantification de couleurs par partition dynamique",
booktitle = "Actes de la journ{'e}e Couleur et Informatique Graphique",
year = 1995,
address = "Lille ",
month = "Mars",
url = {article(.ps.gz):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/articleLILLE.ps.gz},
theme = {quantification},
abstract = "La quantification de couleurs est un probl{`e}me qui
bien qu'il admette d'autres applications a pris de
plus en plus d'importance au fur et {`a} mesure du
d{'e}veloppement des {'e}crans couleurs. Nous proposons
dans ce papier diverses am{'e}liorations des
algorithmes de type partitionement dynamique
permettant de diminuer l'erreur de quantification et
de r{'e}duire l'occupation m{'e}moire."
}
@InProceedings{braquelaire-94-1,
author = "Braquelaire, Jean Pierre and Luc Brun",
title = "Une am{'e}lioration des m{'e}thodes de quantification de
couleur par partition dynamique",
pages = "247-261",
booktitle = "Deuxi{`e}mes journ{'e}es de l'association francc{a}ise
d'informatique graphique ",
year = 1994,
organization = "A.F.I.G",
address = "Toulouse",
theme = {quantification},
abstract = "La quantification de couleurs est un probl{`e}me qui
bien qu'il admette d'autres applications a pris de
plus en plus d'importance au fur et {`a} mesure du
d{'e}veloppement des {'e}crans couleurs. Ce papier se
propose de revoir les principes des techniques de
quantification par partitionnement. Nous d{'e}gagerons
de ceux-ci quelques id{'e}es fortes qui nous
permettront de proposer un nouvel algorithme qui, s'
inscrivant dans la continuit{'e} des algorithmes
d{'e}j{`a} d{'e}velopp{'e}s, affiche des performances tant
en qualit{'e} qu'en espace m{'e}moire et temps de calcul
tout {`a} fait int{'e}ressantes."
}
@PhdThesis{brun-02-9,
author = {Luc Brun},
title = {Traitement d'images couleur et pyramides combinatoires},
school = {Universit{'e} de Reims},
year = 2002,
theme = {topologie,hierarchical,couleur,quantification,inversion},
type = {Habilitation {`a} diriger des recherches},
abstract = "We describe in this thesis three key steps of image
processing algorithms. We first study the reflexion models which
describe the image formation process. These models are used to
obtain a segmentation of the image into materials and to reconstruct
the surface of some of the regions previously segmented. The
materials studded for the reconstruction stage are metallic ones.
We also study quantization and inverse colormap operations. These
operations are used to display an image onto low cost
terminals. Such processes may also be applied into the image
compression or image segmentation framework. We finally describe a
new hierarchical model based on a topological representation of an
image partition. The model named Combinatorial Pyramid is the only
hierarchical model currently developed which allows to encode all
the topological information.",
url= {pdf:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/hdr.pdf,ps.gz:=http://www.greyc.ensicaen.fr/~luc/ARTICLES/hdr.ps.gz}
}
@InBook{brun-02,
author = {Luc {B}run and Alain Tr{'e}meau},
title = {Digital Color Imaging Handbook},
chapter = {9 : Color quantization},
pages = {589-637},
publisher = {CRC Press},
year = 2002,
theme = {quantification,couleur},
series = {Electrical and Applied Signal Processing},
}
@InProceedings{brun-00-2,
author = {Luc {B}run and Myriam Mokhtari},
title = {Two High Speed Color Quantization Algorithms},
booktitle = {Proceedings of CGIP'2000},
pages = {116-121},
year = 2000,
editor = {C{'e}padu{`e}s},
address = {Saint Etienne},
month = {October},
url = {article (.ps):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/cgip.ps, slides(PPT):=http://www.greyc.ensicaen.fr/~luc/ARTICLES/cgip.ppt},
abstract = " Color image quantization has been widely
studied for the last fifteen years. Most of
existing quantization algorithms use pure
top-down or bottom-up approaches, in this
paper we present a two-pass quantization
method using a split stage followed by a merge
one. The split stage uses a uniform
quantization algorithm to generate $N$ initial
clusters. These clusters are then combined
during the merge stage into $K<<N$ final
clusters. Finally, these clusters are used by
an inverse colormap algorithm to create the
output image. Two different inverse colormap
algorithms are proposed leading to two
quantization algorithms. These quantization
algorithms are more efficient than pure split
or pure merge algorithms. Moreover, the
difference between the number of clusters
produced by the split stage and the number of
final clusters allows users to control
efficiently the quality/time ratio.",
theme={quantification}
}
