A fast wavelet-based Karhunen–Loeve transform
| Autor: | Ian R. Greenshields, Joel A. Rosiene |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Discrete wavelet transform
Stationary wavelet transform Second-generation wavelet transform Wavelet transform Wavelet packet decomposition Wavelet Artificial Intelligence Signal Processing Computer Vision and Pattern Recognition Fast wavelet transform Harmonic wavelet transform Algorithm Software Mathematics |
| Zdroj: | Pattern Recognition. 31:839-845 |
| ISSN: | 0031-3203 |
| DOI: | 10.1016/s0031-3203(97)00109-x |
| Popis: | The paper describes the role of the standard wavelet decomposition in computing a fast Karhunen–Loeve transform. The standard wavelet decomposition (which we show is different from the conventional wavelet transform) leads to a highly sparse and simply structured transformed version of the correlation matrix which can be easily subsetted (with little loss of Frobenius norm). The eigenstructure of this smaller matrix can be efficiently computed using standard algorithms such as QL. Finally, we provide an example of the use of the efficient transform by classifying a 219-channel AVIRIS image with respect to its eigensystem. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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