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Intézeti szeminárium
Incorporating a priori information about the solution/desired image
in to the energy-minimization based method is called regularization.
Regularized methods have applications in numerous image processing
problems of different nature, such as discrete tomography, image
denoising or segmentation. Characteristic energy models designed
for these problems will be shown. Special focus will be devoted to
the tomography reconstruction methods. Regularized methods for both
conventional (square) and unconventional (triangular and hexagonal)
image grids will be discussed.