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Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
ISSN: 1058-6393
ISBN: 0-8186-6405-3
pp: 203-207
N. Chaddha , Comput. Syst. Lab., Stanford Univ., CA, USA
Wee-Chiew Tan , Comput. Syst. Lab., Stanford Univ., CA, USA
T.H.Y. Meng , Comput. Syst. Lab., Stanford Univ., CA, USA
ABSTRACT
In many color-imaging applications, it is desirable to display an image with as few different colors as possible with minimal loss in image quality. While good image quality is achievable using traditional vector quantization techniques, they are too slow for real-time video applications. An architectural design of a real-time, scalable color quantizer architecture is presented. It implements our fast tree structure vector quantization algorithm with a variable-size cubical prequantizer based on human perception proposed earlier. The design is scalable and uses different configurations of the processing and memory elements to process any 24-bit to 72-bit colors per input pixel to produce a 8-bit to 24-bit color palette.<>
INDEX TERMS
vector quantisation, real-time systems, video coding, visual perception, image colour analysis
CITATION

N. Chaddha, Wee-Chiew Tan and T. Meng, "A real-time scalable color quantizer trainer/encoder," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 203-207.
doi:10.1109/ACSSC.1994.471445
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