An experiment on texture segmentation using modulated wavelets

A textured image is considered to be produced by a smooth signal, representing in part the illumination environment, modulated by some frequencies determined by surface characteristics of the textures. Through expansion of the smooth signal into wavelets, a textured image may be decomposed into modulated “wavelets” providing multiresolution information. It is shown that the corresponding wavelet coefficients can be obtained efficiently by using the standard wavelet transform while the associated h and g filters are modulated accordingly. A set of multichannel filters is designed through the use of a modulated “wavelet' multiresolution decomposition, providing both spatial frequency and orientation selectivity. Based on these multichannel amplitude responses as discriminating features, an image containing multiple textures can be effectively segmented. The potential of this approach is shown by experimental results