Abstract
In this paper, we present a novel method, which uses non-separable wavelet filter banks, to extract the features of texture images for texture image retrieval. Compared to traditional tensor product wavelets (such as db wavelets), our new method can capture more direction and edge information of texture images, which is highly valuable to reflect the essential properties of the texture images. Experiments show that the proposed method is satisfactory and can achieve better retrieval accuracies than db wavelets.
Original language | English |
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Pages (from-to) | 1501-1510 |
Number of pages | 10 |
Journal | Signal processing |
Volume | 89 |
Issue number | 8 |
Early online date | 10 Feb 2009 |
DOIs | |
Publication status | Published - Aug 2009 |
Keywords
- generalized Gaussian density
- non-tensor product wavelet filter banks
- texture image retrieval
- wavelet