DocumentCode :
1691980
Title :
Statistical wavelet subband modelling for texture classification
Author :
Hill, P.R. ; Canagarajah, C.N. ; Bull, D.R.
Author_Institution :
Bristol Univ., UK
Volume :
1
fYear :
2001
fDate :
6/23/1905 12:00:00 AM
Firstpage :
165
Abstract :
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
Keywords :
content-based retrieval; discrete wavelet transforms; image classification; image retrieval; image texture; parameter estimation; probability; statistical analysis; Bhattacharya metrics; content based image retrieval; discrete wavelet transform; divergence metrics; multivariate distributions; probability density function parameters estimation; spatial-frequency content analysis; statistical analysis; statistical wavelet subband modelling; subband coefficients; texture classification; transform subbands; wavelet packet transforms; wavelet transforms; Content based retrieval; Discrete wavelet transforms; Feature extraction; Hidden Markov models; Image analysis; Image retrieval; Statistical analysis; Wavelet analysis; Wavelet packets; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
Type :
conf
DOI :
10.1109/ICIP.2001.958979
Filename :
958979
Link To Document :
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