Name
Abstract | ||
|---|---|---|
AbstractColor 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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1155/2016/5302957 | Periodicals |
Field | DocType | Volume |
Computer vision,Color histogram,Pattern recognition,Computer science,Self-organizing map,Color balance,Vector quantization,Artificial intelligence,Quantization (image processing),Quantization (signal processing),Color quantization,Octree | Journal | 2016 |
Issue | ISSN | Citations |
1 | 1687-5265 | 1 |
PageRank | References | Authors |
0.35 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyun Jun Park | 1 | 2 | 3.08 |
| kwangbaek kim | 2 | 110 | 43.94 |
| Eui-Young Cha | 3 | 49 | 11.24 |