Comparison of methods of fractal texture extraction for high-resolution remotely sensed images

Till now, there were several methods of fractal texture extraction developed for high-resolution remotely sensed images: triangular prism, fractal Brownian motion, DBC (different box-counting) and multi-fractal. However, one proper method should be selected in application. Upon that, in the paper, taking QuickBird image as example, based on a rather entire classification system founded for the image, fractal dimensions and correlative parameter were utilized to analyze features of those methods; mean, variance and computation time were utilized to compare difference of them. Then several conclusions were drawn through the experiment: fractal texture could be an effective feature to distinguish ground objects; among those methods, triangular prism couldn´t do well on ground objects´ distinguishing, FBM wasn´t accurate (without no-scale part), but DBC and multi-fractal represented better on distinguishing ground objects and computing efficiency.