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# Rn morphological operators

#

# This is basically just a wrapper for various ndimage

#

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#Miscellaneous functions for managing discrete Rn morphology

import scipy as sp;

import scipy.ndimage as ndi;

from numpy.fft import rfftn, irfftn, fftshift, ifftshift;

from indicator import *;

#Computes the support of f

def supp(f):

return vol(f);

#Computes the inverse of f

def invert(f):

return f[tuple(rs)];

#Shifts the function f by the element v in R2

def shift(v, f):

return ndi.shift(f, v);

#Pads an indicator function up to size nd, recentering to origin

def cpad(f, nd):

return fftshift(pad(f,nd));

#Convolution over Rn

def conv(f, g):

return res;

#Correlation/homogeneous convolution over Rn

def hg_conv(f, g):

return res;

#Minkowski sum over Rn

def mink_sum(f,g):

return to_ind(conv(f,g), 1);

#Minkowski difference over Rn

def mink_diff(f,g):

return to_ind(conv(f,g), supp(g) - 1);

#Homogeneous Minkowski sum

def hg_mink_sum(f,g):

return to_ind(hg_conv(f, g), 1);

#Homogeneous Minkowski left difference

def hg_mink_ldiff(f,g):

return to_ind(conv(f,g), supp(g) - 1);

#Homogeneous Minkowski right difference

def hg_mink_rdiff(f,g):

return to_ind(conv(f,g), supp(f) - 1);