Title :
Robust estimation of image fractal dimension based on pyramidal decomposition
Author :
Aiazzi, B. ; Alparone, L. ; Baronti, S. ; Bulletti, A. ; Garzelli, A.
Author_Institution :
Ist. di Ricerca sulle Onde Elettromagnetiche, CNR, Firenze, Italy
Abstract :
An approach to calculate the fractal dimension of images comes from power spectra of fractional Brownian motions: the ratio between powers at different scales is related to the persistence parameter H and, thus, to the fractal dimension D=3-H. The signal-dependent nature of speckle noise, however, prevents a correct estimation of fractal dimension from synthetic aperture radar (SAR) images. Here, we propose and assess a novel method to obtain D based on the multi-scale decomposition provided by the normalized Laplacian pyramid (NLP), which is a bandpass representation obtained by dividing the layers of an LP by its expanded baseband and designed to yield noise that is signal-independent. Experiments on both synthetic and true SAR images corroborate the underlying assumptions
Keywords :
Brownian motion; fractals; radar imaging; radar theory; synthetic aperture radar; SAR images; bandpass representation; expanded baseband; fractional Brownian motions; image fractal dimension; multi-scale decomposition; normalized Laplacian pyramid; persistence parameter; power spectra; pyramidal decomposition; signal-dependent nature; synthetic aperture radar; Baseband; Electrons; Fractals; Laplace equations; Radar imaging; Robustness; Rough surfaces; Signal to noise ratio; Speckle; Surface roughness;
Conference_Titel :
Electronics, Circuits and Systems, 1999. Proceedings of ICECS '99. The 6th IEEE International Conference on
Conference_Location :
Pafos
Print_ISBN :
0-7803-5682-9
DOI :
10.1109/ICECS.1999.812345