Name
Abstract | ||
|---|---|---|
Today, almost all of the implementations of the discrete wavelet transforms are based on the recursive way. However, non-recursive wavelet transforms (NRWT) are more effective and more flexible. We extend the NRWT theory in l^2 (Z) and propose a new NRWT theory based on 6 different downsampling modes in l^2 (Z_c^+ ). This extending makes NRWT more practical and can be compatible with the traditional recursive wavelet transform. We study the properties of the NRWT under the 6 downsampling modes, W_(-3≤k≤2), through the analysis of redundancy degree and point out that W_(-2) is optimal and the redundancy degrees of W_(-2) and W_0 are identical. The analysis of redundancy degree offers a method to choose the NRWT mode. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/PACIIA.2008.45 | PACIIA (1) |
Keywords | Field | DocType |
discrete wavelet transform,wavelet transform | Lifting scheme,Computer science,Theoretical computer science,Artificial intelligence,Discrete wavelet transform,Wavelet packet decomposition,Wavelet,Wavelet transform,Pattern recognition,Algorithm,Second-generation wavelet transform,Cascade algorithm,Stationary wavelet transform | Conference |
Volume | Citations | PageRank |
1 | 0 | 0.34 |
References | Authors | |
3 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoxin Li | 1 | 0 | 2.03 |
| De-yu Qi | 2 | 64 | 16.54 |
| Zhengping Qian | 3 | 350 | 17.04 |