Fast color image quantization using squared euclidean distance of adjacent color points along the highest color variance axis

被引：0
|
作者：
Sirisathitkul, Y [1 ]
Auwatanamongkol, S [1 ]
Uyyanonvara, B [1 ]
机构：
[1] Natl Inst Dev Adm, Sch Appl Stat, Bangkok, Thailand
来源：
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 1 | 2004年
关键词：
D O I：
10.1109/ICPR.2004.1334251
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new color image quantization algorithm that uses the squared Euclidean distance of adjacent color points along the highest color variance axis is proposed This algorithm is a hierarchically divisive colormap design technique. Colors are sorted along the axis with the highest variance of color distribution. The squared Euclidean distances between any adjacent colors' along the axis are then used to find the cutting plane that divides a color cell into two subcells with approximately equal quantization errors respect to their centroids. The proposed algorithm is effective and yields a short execution time.
引用
收藏
页码：656 / 659
页数：4
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