Name
Abstract | ||
|---|---|---|
Texture classification plays an important role in image analysis. The wavelet transform is a very efficient multiscale analysis method that has been successfully applied to describe the texture. The double-density dual-tree wavelet transform can simultaneously possess the properties of the double-density discrete wavelet transform (DWT) and the dual-tree DWT. In this paper, the texture feature based on the double-density dual-tree wavelet transform are derived from the subbands and tested in two benchmark texture databases. The experimental results suggest the potential capacity of the double-density dual-tree wavelet transform in texture analysis. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/IIH-MSP.2009.148 | IIH-MSP |
Keywords | Field | DocType |
benchmark texture databases,important role,double-density dual-tree,texture classification,double-density discrete wavelet,double-density dual-tree wavelet transform,image analysis,dual-tree dwt,efficient multiscale analysis method,texture analysis,databases,wavelet transform,discrete wavelet transform,image classification,image texture,shift invariant,wavelet analysis,computational complexity,feature extraction | Computer vision,Harmonic wavelet transform,Pattern recognition,Lifting scheme,Computer science,Second-generation wavelet transform,Artificial intelligence,Discrete wavelet transform,Stationary wavelet transform,Wavelet packet decomposition,Wavelet transform,Wavelet | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiao Yu-Long | 1 | 17 | 3.22 |
| chunyan song | 2 | 0 | 0.34 |
| chunhui zhao | 3 | 0 | 0.34 |