Vector choice in the texture spectrum approach

Abstract

Recently the texture spectrum approach has been proposed as a statistical method for texture analysis, and applied to remotely sensed images. In the present study, this method is generalized to a space of M vectors and N grey level intervals for the elements of texture units, instead of M = 8 and N = 3 in the earlier studies of the texture spectrum. In this way, the texture unit set can be defined in a neighbourhood of 3 pixels by 3 pixels, 5 pixels by 5 pixels, 7 pixels by 7 pixels or other forms and sizes, and the co-occurrence matrix approach is unified to the texture spectrum method with the extreme case of M = 1. Several combinations of M and N have been evaluated to classify an imagery composed of six natural textures. The results show maximum discrimination for M = 5, followed by M = 4. In this way we minimize the calculation lime needed to maximize the accuracy of the classification.