1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
|
Total Variation
===============
This section deals with an iterative reconstruction algorithm (hence,
different from the filtered back projection), that solves the
minimization problem ::
x = argmin 1/2||H x - y||^2 + beta_tv TV(x)
where:
* x is the image to be reconstructed
* H is the projection matrix
* y is the sinogram
* TV(x) is the total variation semi-norm of x, that is, the l1 norm of
its gradient
* beta_tv is a parameter controlling the relative importance of the two
terms in the minimization
This algorithm tends to reconstruct piecewise-constant images. It is
therefore suitable for images with a limited number of phases, such as
many images in materials science. It is not suited, however, for images
with a very irregular texture, or for images with smooth large-scale
gradients.
*The following documentation has been extracted automatically from the comments found in the source code. Discard Parameters. object variable.*
.. automodule:: Parameters_module
:noindex:
.. autoclass:: Parameters
:members: ITERATIVE_CORRECTIONS,DO_PRECONDITION, FISTA,DENOISING_TYPE,ITERATIVE_CORRECTIONS_NOPREC,BETA_TV, N_ITERS_DENOISING, DUAL_GAP_STOP, OPTIM_ALGORITHM
|
