Multiresolutional texture analysis of multispectral imagery for automated ground cover classification

The authors provide an introduction to wavelet-based texture recognition. The authors compare conventional approaches, such as co-occurrence matrix methods and Fourier-based techniques, to wavelet-based approaches. Practical remote sensing applications are presented, including the detection of weeds in agricultural crops and the detection and analysis of noxious weeds for environmental applications. For these case studies, the authors present a theoretical discussion as well as experimental classification results. These applications demonstrate the benefits of multiresolutional methods to the texture classification task in multispectral imagery.