7 research outputs found
Efficient binary tomographic reconstruction
Tomographic reconstruction of a binary image from few projections is
considered. A novel {\em heuristic} algorithm is proposed, the central element
of which is a nonlinear transformation of the
probability that a pixel of the sought image be 1-valued. It consists of
backprojections based on and iterative corrections. Application of
this algorithm to a series of artificial test cases leads to exact binary
reconstructions, (i.e recovery of the binary image for each single pixel) from
the knowledge of projection data over a few directions. Images up to
pixels are reconstructed in a few seconds. A series of test cases is performed
for comparison with previous methods, showing a better efficiency and reduced
computation times
Projection selection dependency in binary tomography
It has already been shown that the choice of projection angles can significantly influence the quality of reconstructions in discrete tomography. In this contribution we summarize and extend the previous results by explaining and demonstrating the effects of projection selection dependency, in a set of experimental software tests. We perform reconstructions of software phantoms, by using different binary tomography reconstruction algorithms, from different equiangular and non-equiangular projections sets, under various conditions (i.e., when the objects to be reconstructed undergo slight topological changes, or the projection data is affected by noise) and compare the results with suitable approaches. Based on our observations, we reveal regularities in the resulting data and discuss possible consequences of such projection selection dependency in binary tomography