@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):=https://brunl01.users.greyc.fr/ARTICLES/cgip.ps, slides(PPT):=https://brunl01.users.greyc.fr/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}
}
@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},
  url=           {ResearchGate:=https://www.researchgate.net/publication/229476136_Digital_Color_Imaging_Handbook}
}
@Unpublished{brun-02-8,
  author = 	 {Luc Brun},
  title = 	 {Traitement d'images couleur},
  year =	 2002,
  url =          {link to my lectures := https://brunl01.users.greyc.fr/ENSEIGNEMENT/enseignement.html},
  theme =        {couleur}
}
@InProceedings{brun-97-3,
  author = 	 {Luc {B}run and Claude Secroun},
  title = 	 {Une nouvelle m{\'e}thode d'inversion de tables de couleurs},
  booktitle = 	 {journ{\'e}es de l'association franc\c{a}ise
		  d'informatique graphique },
  year =	 1997,
  address =	 {Rennes},
  theme =        {inverse},
  organization = {A.F.I.G.},
  url=           {article(.ps):=https://brunl01.users.greyc.fr/ARTICLES/afig97.ps.gz},
  abstract =     "L'inversion de la table de couleurs est un processus
		 permettant de cr{\'e}er une image {\`a} partir d'une
		 image d'entr{\'e}e et d'un ensemble de couleurs
		 appel{\'e} la table de couleurs ou l'ensemble des
		 couleurs repr{\'e}sentatives. Afin de diminuer la
		 distance visuelle entre l'image d'entr{\'e}e et l'image
		 r{\'e}sultat, ce processus affecte {\`a} chaque couleur
		 de l'image originale sa couleur la plus proche dans
		 la table de couleurs. La m{\'e}thode que nous allons
		 pr{\'e}senter est bas{\'e}e sur une projection de
		 l'ensemble des couleurs de l'image sur un plan
		 discret. L'utilisation de ce plan nous permet
		 d'approximer efficacement le diagramme de Voronoi 3D
		 sous-jacent aux m{\'e}thodes d'inversion de table de
		 couleurs."
}

@Article{brun-99,
  author = 	 {Luc {B}run  and Claude Secroun},
  title = 	 {A fast algorithm for inverse color map computation},
  journal = 	 {Computer Graphics Forum},
  year = 	 1998,
  volume =	 17,
  number =	 4,
  pages =	 {263-271},
  theme =        {inverse},
  month =	 {December},
  url =          {article:=https://brunl01.users.greyc.fr/cgf.ps.gz},
  abstract =     "The inverse colormap operation is the process
		    which allows an image to be displayed with a
		    limited set of colors. In order to obtain minimal
		    visual distortion between the input image and the
		    displayed image, inverse colormap algorithms
		    associate each color with its nearest
		    representative. The method presented in this paper
		    is based on a Karhunen-Lo{\`e}ve transformation,
		    which allows us to efficiently approximate the 3D
		    Voronoi diagram implicitly used by inverse color
		    map algorithms by its 2D projection into the plane
		    defined by the first two eigenvectors of the
		    covariance matrix and then performing an
		    additional correction step. The complexity of our
		    algorithm is independent of the size of the
		    colormap. Moreover, its results are equal or quite
		    close to the optimal solution."
}


@InProceedings{hussenet-02-1,
  author = 	 {Laurent Hussenet and Luc Brun},
  title = 	 {Reconstruction of Shiny objects},
  booktitle = 	 {Proceedings of  the International Conference on Computer Vision and Graphics},
  pages =        {337-342},
  year =	 2002,
  editor =       {Konrad Wojciechowseki},
  address =	 {Zakopane, Poland},
  month =	 {September},
  theme = {couleur}
}
@InProceedings{hussenet-01,
  author = 	 {Laurent Hussenet and Luc {B}run},
  title = 	 {Physic Based Classification for Color Images},
  booktitle = 	 {Physics in Signal \& Image Processing},
  pages =	 {173-176},
  year =	 2001,
  address =	 {Marseille},
  month =	 {January},
  organization = {Soci{\'e}t{\'e} de l'{\'E}lectricit{\'e}, de l'{\'E}lectronique et des Technologies de l'Information et de la Communication},
  url=           {article :=https://brunl01.users.greyc.fr/ARTICLES/psip_final.pdf},
  abstract = "	This paper presents a new method for segmenting color
		images into regions composed of an unique
		material. This method is based on a spectral
		reflection model and a characterization of the camera
		used for acquisitions. The study of these crucial
		points of the acquisition process allows us to define
		expressions which remain constants for all pixels's
		color corresponding to a same material. These
		constants are then used in the color segmentation
		process.",
  theme=         {couleur}
}

@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 franc\c{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."
}

@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):=https://brunl01.users.greyc.fr/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."
}
@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) :=https://brunl01.users.greyc.fr/ARTICLES/articleIEEE.ps.gz, article(.ps) :=https://brunl01.users.greyc.fr/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."
}