Abstract
In this paper, an application of Quadrature Mirror Filter (QMF) bank-based subband decomposition to texture analysis is presented. Two-dimensional 4-band QMF structure is used and the QMF features are introduced such that the low-low band extracts the information of spatial dependence and the low-high, high-low, and high-high bands extract the structural information. This approach has the twin advantages of efficient information extraction and parallel implementation. The classification abilities of QMF features are compared to those of Haralick features. The experiments demonstrate that the QMF features have better performance than the Haralick features.
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