OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) Computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.
This functions Computes SARMA or multiplicative (p,q) x (P,Q) models for
(p,q,P,Q) in (pvec x qvec x Pvec x Qvec) it returns the best according to AIC
where AIC has been modified to account for fixed parameters
x = input data
pvec = vector of p s set pvec=[0] for no AR
qvec = vector of q s set qvec=0[] for no MA
Pvec = vector of P s
Qvec = vector of Q s
T period for multiplicative model
Defines and Computes the Differentiation Kernel, the kernel of the inverse heat conduction problem as a function of s and r. Note: you will need to select some value Nmax at which to terminate the infinite sums in SVE of the kernel
