Performance Improvement of Fractal Dimension Estimator Based on a New Sampling Method

Title & Authors
Performance Improvement of Fractal Dimension Estimator Based on a New Sampling Method
Jin, Gang-Gyoo; Choi, Dong-Sik;

Abstract
Fractal theory has been widely used to quantify the complexity of remotely sensed digital elevation models and images. Despite successful applications of fractals to a variety of fields including computer graphics, engineering and geosciences, the performance of fractal estimators depends highly on data sampling. In this paper, we propose an algorithm for computing the fractal dimension based on the triangular prism method and a new sampling method. The proposed sampling method combines existing two methods, that is, the geometric step method and the divisor step method to increase pixel utilization. In addition, while the existing estimation methods are based on $\small{N{\times}M}$ window, the proposed method expands to $\small{N{\times}M}$ window. The proposed method is applied to generated fractal DEM, Brodatz's image DB and real images taken in the campus to demonstrate its feasibility.
Keywords
digital elevation model(DEM);fractal dimension;data sampling;triangular prism method;
Language
Korean
Cited by
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