Texture classification using wavelet scale relationships
It has been documented in the literature that texture can be well characterised by features obtained from its multi-scale representation. Typically, the textured image being analysed is decomposed into separate frequency and/or orientation bands, and features extracted separately from each such band. In this paper, we propose that features modelling the relationships between scale bands of such a representation provide a better characterisation of textured images than features extracted from individual bands alone. Using this conjecture, we develop a novel feature set for texture classification, and demonstrate its effectiveness using a set of images obtained from the Brodatz texture album.