On-line construction of the convex hull of a simple polyline
Information Processing Letters
Fractals everywhere
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Fractal geometry analysis of turbulent data
Signal Processing
Computational geometry in C (2nd ed.)
Computational geometry in C (2nd ed.)
On the parameter identification problem in the plane and polar fractal interpolation functions
Journal of Approximation Theory
A new Hausdorff distance for image matching
Pattern Recognition Letters
Using iterated function systems to model discrete sequences
IEEE Transactions on Signal Processing
Efficient computation of the Hutchinson metric between digitized images
IEEE Transactions on Image Processing
Journal of Mathematical Imaging and Vision
Hi-index | 7.29 |
Fractal interpolation functions are very useful in capturing data that exhibit an irregular (non-smooth) structure. Two new methods to identify the vertical scaling factors of such functions are presented. In particular, they minimize the area of the symmetric difference between the bounding volumes of the data points and their transformed images. Comparative results with existing methods are given that establish the proposed ones as attractive alternatives. In general, they outperform existing methods for both low and high compression ratios. Moreover, lower and upper bounds for the vertical scaling factors that are computed by the first method are presented.