A fast pixel mapping algorithm using principal component analysis

Authors:
Kuo-Feng Hwang;Chin-Chen Chang
Affiliations:
Department of Computer Science and Information Engineering, National Chung Cheng University, 160 San-Hsing, Min-Hsiung, Chaiyi 621, Taiwan;Department of Computer Science and Information Engineering, National Chung Cheng University, 160 San-Hsing, Min-Hsiung, Chaiyi 621, Taiwan
Venue:
Pattern Recognition Letters
Year:
2002

Citing 3
Cited 2

Vector quantization and signal compression

Vector quantization and signal compression
Color image compression using quantization, thresholding, and edge detection techniques all based on the moment-preserving principle

Pattern Recognition Letters
Fast VQ encoding by an efficient kick-out condition

IEEE Transactions on Circuits and Systems for Video Technology

Color image quantization using distances between adjacent colors along the color axis with highest color variance

Pattern Recognition Letters
Information-preserving hybrid data reduction based on fuzzy-rough techniques

Pattern Recognition Letters

Quantified Score

Hi-index	0.10

Visualization

Abstract

Pixel mapping is one of the basic processes in color quantization. In this paper, we shall propose a new algorithm using principal component analysis as a faster approach to pixel mapping. Within much shorter search time, our new scheme can find the nearest color which is identical to the one found using a full search. The idea behind the proposed method is quite simple. First, we compute two principal component directions (PCDs) for the palette. Then, the projected values on PCDs are computed for each color in palette. Finally, the projected values, following the triangular inequality principle, can help us reduce the computation time for finding the nearest color. The experimental results reveal that the proposed scheme is more efficient than the previous work.