Understanding the inner workings of the radon function (from skimage)
Kaloyan Marinov
kaloyan.at.uw at gmail.com
Thu Apr 10 07:25:07 EDT 2014
I am familiar with the mathematical theory of the continuous Radon
transform, but am having trouble understanding its discrete implementation
from skimage. Below I list my two questions on the topic.
*Question 1*
Let us define a matrix A as follows:
A = np.zeros( (4,4) )
A[1:3,1:3] = 1
Compute its Radon transform as follows:
radTranfOfA = skimage.transform.radon(A,[45])
This computed radTranfOfA to be the following array of shape (6,1):
array([[ 0. ],
[ 0. ],
[ 0.87867966],
[ 2.42893219],
[ 0.87867966],
[ 0. ]])
Could someone explain to me (preferably in a mathematically precise way)
exactly how Python computed this?
*Question 2*
I have attempted to study the radon_transform.py source-code file from the
skimage package, but the definition of the radon function there depends on
a function called _warp_fast which is imported from _warps_cy. However, I
cannot see the sourcecode for _warps_cy; could anyone suggest a way around
this (or a precise mathematical explanation of what _warps_cy does and how
its output is stored)?
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