Oppgavetekst til kontrakten

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+Anisotropic total variation based image restoration using graph cuts
+
+Anisotropic diffusion and total variation are two popular methods in
+image restoration, where the goal is to remove noise from a captured
+image. They are both popular because of their ability to preserve edges
+in the original image, but also have certain problems. Anisotropic
+diffusion filtering may introduce new structures from the noise, while
+total variation filtering may reduce the contrast near corners and thin
+structures. The objective of the thesis is to introduce an anisotropic
+total variation norm enforcing strong regularization along edges and
+weak regularization across edges. The resulting energy function will
+then be minimized using a graph cut approach based on the one that is
+popular in regular total variation filtering. In the anisotropic
+setting, the necessary edge weights can be constructed by using an
+anisotropic variant of the Cauchy Crofton formula. The resulting method
+is then be compared to regular anisotropic diffusion and total variation
+filtering.
+