An Effective Color Quantization Method Using Octree-Based Self-Organizing Maps. (14th January 2016)

• Record Type: Journal Article
• Authors: Park, Hyun Jun; Kim, Kwang Baek; Cha, Eui-Young
• Other Names: Tanaka Toshihisa Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2016(2016)
• Publication Date: 2016-01-14
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2016/5302957
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : 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.