0
Regular Articles

Adaptive color quantization using the “baker’s transformation”

[+] Author Affiliations
Christophe Montagne

University of Evry-Val d’Essonne, Informatique, Biologie Intégrative et Systémes Complexes (IBISC) Laboratory, Centre National de la Recherche Scientifique (CNRS) FRE 2873, 40 rue du Pelvoux, 91020 Evry Cedex, France

André Smolarz

University of Technology of Troyes, Institut des Sciences et Technologies de l'Information de Troyes (ISTIT) Laboratory, CNRS FRE 2732, 12 rue Marie Curie BP 2060, 10010 Troyes Cedex, France

Mohamed Chaker Larabi, Christine Fernandez-Maloigne

University of Poitiers, Institut de Recherche en Communications Optiques et Microondes — Signal, Image, Communications (IRCOM-SIC), CNRS FRE 2731, BP 30179, 86962 Futuroscope Chasseneuil Cedex, France

Philippe Cornu

University of Technology of Troyes, Institut des Sciences et Technologies de l'Information de Troyes (ISTIT) Laboratory, CNRS FRE 2732, 12 rue Marie Curie BP 2060, 10010 Troyes Cedex, France

Sylvie Lelandais

University of Evry-Val d’Essonne, Informatique, Biologie Intégrative et Systémes Complexes (IBISC) Laboratory, Centre National de la Recherche Scientifique (CNRS) FRE 2873, 40 rue du Pelvoux, 91020 Evry Cedex, France

J. Electron. Imaging. 15(2), 023015 (May 22, 2006). doi:10.1117/1.2199854
History: Received September 13, 2004; Revised October 10, 2005; Accepted October 28, 2005; Published May 22, 2006
Text Size: A A A

We propose an original technique to reduce the number of colors contained in an image. This method uses the “baker’s transformation,” which obtains a statistically suitable mixture of the pixels of the image. From this mixture, we can extract several samples, which present the same characteristics as the initial image. The concept we imagine is to consider these samples as potential pallets of colors. These pallets make it possible to do an adaptive quantization of the effective number of colors. We consider, and we put in competition, three methods to obtain a single pallet. We present the baker’s transformation and we present methods to have a single pallet. The results illustrate the good visual quality reached by the quantized images. Finally, we present a comparison between our method and three classical methods of quantization.

© 2006 SPIE and IS&T

Topics

Quantization

Citation

Christophe Montagne ; André Smolarz ; Mohamed Chaker Larabi ; Christine Fernandez-Maloigne ; Philippe Cornu, et al.
"Adaptive color quantization using the “baker’s transformation”", J. Electron. Imaging. 15(2), 023015 (May 22, 2006). ; http://dx.doi.org/10.1117/1.2199854


Access This Article
Sign In to Access Full Content
Please Wait... Processing your request... Please Wait.
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
 
Your Session has timed out. Please sign back in to continue.
Sign In to Access Full Content

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement

Buy this article ($18 for members, $25 for non-members).
Sign In