DocumentCode
3345549
Title
A New Human Perceptional Color Quantization Algorithm
Author
Chen Lixia
Author_Institution
Sch. of Sci., Xidian Univ., Xi´an, China
fYear
2009
fDate
14-17 Oct. 2009
Firstpage
710
Lastpage
713
Abstract
The goal of color quantization is to remarkably reducing the number of colors in an image without obviously degrading its visual effect. The study of this paper proposed a new human perceptional color quantization algorithm which minimizing the quantization distortion under the perceptually uniform Munsell NBS distance measurements. This method chooses the most frequently used colors as seeds with a limitation of the optimal minimal distance between seeds, which is computed using an iterative algorithm. Experiments show that the proposed method outperforms the minimal variance quantization (MVQ) algorithm on quantization distortion and perceptual effect.
Keywords
image coding; image colour analysis; iterative methods; human perceptional color quantization algorithm; image colors; iterative algorithm; minimal variance quantization algorithm; perceptually uniform Munsell NBS distance measurements; quantization distortion minimization; visual effect; Clustering algorithms; Degradation; Humans; Image color analysis; Iterative algorithms; NIST; Nonlinear distortion; Pixel; Quantization; Visual effects;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location
Guilin
Print_ISBN
978-0-7695-3899-0
Type
conf
DOI
10.1109/WGEC.2009.84
Filename
5402809
Link To Document