The definition and rendering of terrain maps
SIGGRAPH '86 Proceedings of the 13th annual conference on Computer graphics and interactive techniques
The geometry of fractal sets
Texture Segmentation Using Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer rendering of stochastic models
Communications of the ACM
An improved algorithm for computing local fractal dimension using the triangular prism method
Computers & Geosciences
A comparison of fractal dimension estimators based on multiple surface generation algorithms
Computers & Geosciences
The Image Processing Handbook, Sixth Edition
The Image Processing Handbook, Sixth Edition
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We present a new method for computing the local fractal dimension in remote sensing imagery. It is based on a novel way of estimating the quadratic self correlation (or 2D Hurst coefficient) of the pixel values. The method is thoroughly tested with a set of synthetic images an also with remote sensing imagery to assess the usefulness of the techniques for unsupervised image segmentation. We make a comparison with other estimators of the local fractal dimension. Quadratic self-correlation methods provide more accurate results with synthetic images, and also produce more robust and fit segmentations in remote sensing imagery. Even with very small computation windows, the methods prove to be able to detect borders and details precisely.