P. Charbonnier et al., DETERMINISTIC EDGE-PRESERVING REGULARIZATION IN COMPUTED IMAGING, IEEE transactions on image processing, 6(2), 1997, pp. 298-311
Citations number
32
Categorie Soggetti
Computer Sciences, Special Topics","Engineering, Eletrical & Electronic","Computer Science Software Graphycs Programming","Computer Science Theory & Methods
Many image processing problems are ill posed and must be regularized,
Usually, a roughness penalty is imposed on the solution, The difficult
y is to avoid the smoothing of edges, which are very important attribu
tes of the image. In this paper, we first give conditions for the desi
gn of such an edge-preserving regularization. Under these conditions,
me show that it is possible to introduce an auxiliary variable whose r
ole is twofold, First, it marks the discontinuities and ensures their
preservation from smoothing, Second, it makes the criterion half-quadr
atic. The optimization is then easier, We propose a deterministic stra
tegy, based on alternate minimizations on the image and the auxiliary
variable, This Leads to the definition of an original reconstruction a
lgorithm, called ARTUR, Some theoretical properties of ARTUR are discu
ssed, Experimental results illustrate the behavior of the algorithm, T
hese results are shown in the field of tomography, but this method can
be applied in a large number of applications in image processing.