Clustering with K-Harmonic Means Applied to Colour Image Quantization

Author

Frackiewicz, Mariusz ; Palus, Henryk

Author_Institution

Inst. of Autom. Control, Silesian Univ. of Technol., Gliwice

fYear

2008

fDate

16-19 Dec. 2008

Firstpage

52

Lastpage

57

Abstract

The main goal of colour quantization methods is a colour reduction with minimum colour error. In this paper were investigated six following colour quantization techniques: the classical median cut, improved median cut, clustering k-means technique in two colour versions (RGB, CIELAB) and also two versions of relative novel technique named k-harmonic means. The comparison presented here was based on testing of ten natural colour images for quantization into 16, 64 and 256 colours. In evaluation process two criteria were used: the mean squared quantization error (MSE) and the average error in the CIELAB colour space (DeltaE). During tests the efficiency of k-harmonic means applied to colour quantization has been proved.

Keywords

image coding; image colour analysis; mean square error methods; pattern clustering; quantisation (signal); CIELAB colour space; classical median cut; clustering k-means technique; colour image quantization; improved median cut; k-harmonic means; mean squared quantization error; Automatic control; Clustering algorithms; Color; Image coding; Image processing; Iterative algorithms; Iterative methods; Pixel; Quantization; Testing; clustering; colour image quantization; k-harmonic means; k-means; quality measures;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Information Technology, 2008. ISSPIT 2008. IEEE International Symposium on

Conference_Location

Sarajevo

Print_ISBN

978-1-4244-3554-8

Electronic_ISBN

978-1-4244-3555-5

Type

conf

DOI

10.1109/ISSPIT.2008.4775684

Filename

4775684