Description: Functions to fit a 2D Gaussian or 2D Gabor to a surface. The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters. This is done by evaluating the quality of fit (sum of squared error) for many different choices of parameters then refining the most promising set of params through least-squares (exhaustive search followed by refinement). Least-squares is statistically equivalent to maximum likelihood estimation of the model parameters on the assumption of independent, normally distributed Gaussian noise in the observations (pixels).
autoGaussianSurf(xi,yi,zi) fits a Gaussian,
To Search:
File list (Check if you may need any files):
TryAutoGaussianSurf.m
autoGaborSurf.m
autoGaussianSurf.m
autoGaussianSurfMH.m
license.txt
readme.txt
Download