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Bregmanized (Higher Order) Total Variation and its Application in PET

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If you have a question about this talk, please contact Carola-Bibiane Schoenlieb.

One of the standard techniques in image denoising – the ROF -model – is well known for recovering sharp edges of a signal or image, but also for producing staircase-like artifacts and suffering from a loss of contrast. In order to overcome these model-dependent deficiencies, total variation (TV) modifications that incorporate higher-order derivatives have been proposed. These approaches reduce staircasing for reasonable parameter choices. However, the loss of contrast remains but can be eliminated in all models by using Bregman iterations. In the second part of the talk the presented methods are applied to image reconstruction in Positron Emission Tomography (PET).

This talk is part of the Cambridge Image Analysis Seminars series.

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