Simple wavelet and wavelet packet transforms have often been used for texture characterisation through the analysis of spatial-frequency content. However, most previous methods make no use of any statistical analysis of the transforms' subbands. A novel method is now presented for modelling the multivariate distributions of subband coefficients by considering spatially related coefficients. The Bhattacharya and divergence metrics are then used to produce an improved texture classification method for the application to content based image retrieval.
|Translated title of the contribution||Statistical Wavelet Subband Modelling for Texture Classification|
|Title of host publication||ICIP 2001|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Pages||165 - 168|
|Publication status||Published - Oct 2001|
|Event||International Conference on Image Processing, 2001 (ICIP 2001) - Thessaloniki, Greece|
Duration: 1 Oct 2001 → …
|Conference||International Conference on Image Processing, 2001 (ICIP 2001)|
|Period||1/10/01 → …|
Bibliographical noteRose publication type: Conference contribution
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