Fractal dimension estimation using continuous alternating sequential filter pyramid

Author

Swarnakar, Vivek ; Acharya, Raj S.

Author_Institution

Dept. of Electr. & Comput. Eng., State Univ. of New York, Buffalo, NY, USA

Volume

3

fYear

1995

fDate

23-26 Oct 1995

Firstpage

652

Abstract

One of the basic characteristics of a fractal is its dimension. Estimates of the dimension tend to be very inaccurate, as data size is reduced. This paper presents a novel method for fractal dimension estimation based on the use of continuous pyramids of alternative sequential filters (CASF). The method assumes only the self-similarity property of fractals. It was tested over synthetic images and results are presented. Performance of CASF was compared to that of the power spectra method and the wavelet method for large size images (512×512). Results show that CASF yields much more accurate estimates than the other two methods. When applied to small images, (16×16) it was observed that the accuracy of the method was still comparable to that obtained with large images

Keywords

filtering theory; fractals; image processing; parameter estimation; continuous alternating sequential filter pyramid; data size; fractal dimension estimation; large size images; self-similarity property; synthetic images; Biomedical imaging; Chaos; Filters; Fractals; Image restoration; Testing; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1995. Proceedings., International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-8186-7310-9

Type

conf

DOI

10.1109/ICIP.1995.537719

Filename

537719