An Effective Color Quantization Method Using Octree-Based Self-Organizing Maps

Joint Authors

Kim, Kwang Baek
Park, Hyun Jun
Cha, Eui-Young

Source

Computational Intelligence and Neuroscience

Issue

Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-01-14

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Biology

Abstract EN

Color quantization is an essential technique in color image processing, which has been continuously researched.

It is often used, in particular, as preprocessing for many applications.

Self-Organizing Map (SOM) color quantization is one of the most effective methods.

However, it is inefficient for obtaining accurate results when it performs quantization with too few colors.

In this paper, we present a more effective color quantization algorithm that reduces the number of colors to a small number by using octree quantization.

This generates more natural results with less difference from the original image.

The proposed method is evaluated by comparing it with well-known quantization methods.

The experimental results show that the proposed method is more effective than other methods when using a small number of colors to quantize the colors.

Also, it takes only 71.73% of the processing time of the conventional SOM method.

American Psychological Association (APA)

Park, Hyun Jun& Kim, Kwang Baek& Cha, Eui-Young. 2016. An Effective Color Quantization Method Using Octree-Based Self-Organizing Maps. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099699

Modern Language Association (MLA)

Park, Hyun Jun…[et al.]. An Effective Color Quantization Method Using Octree-Based Self-Organizing Maps. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1099699

American Medical Association (AMA)

Park, Hyun Jun& Kim, Kwang Baek& Cha, Eui-Young. An Effective Color Quantization Method Using Octree-Based Self-Organizing Maps. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099699

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1099699