estimOSC2DH

Computes the Pointwise Holder exponent based on a method that uses oscillations for a 2D signal (an image)

Syntax

H = estimOSC1DH(x,base,alpha,beta)
H = estimOSC2DH(...,'Regression type')
H = estimOSC2DH(...,'Propertyname',Propertyvalue)

Description

H = estimOSC2DH(x,base,alpha,beta) Estimates the Holder function, H of the input signal x, using a least square regression. The parameters alpha and beta are real values in (0:1) which characterize the neighborhood of each point where the exponent is computed. For each point the Holder exponent is estimated using a neighborhood of points.

H = estimOSC2DH(...,'Regression type') Estimates the Holder function, H, using a specific type of regression. The Regression Type can be choosen from the list below :

H = estimOSC2DH(...,'Propertyname',Propertyvalue) returns the estimator H applying the specified property settings. The Property setting can be choosen from the list below:

Examples

See Also

estimGQV2DH

References

[1] C. Tricot, "Curves and Fractal Dimension" Springer-Verlag (1995).

[2] O. Barrière, "Synthèse et estimation de mouvements Browniens multifractionnaires et autres processus à régularité prescrite. Définition du processus autorégulé multifractionnaire et applications", PhD Thesis (2007).