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Second- versus fourth-order dynamics in imaging

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If you have a question about this talk, please contact Rachel Fogg .

Nonlinear partial differential equations (PDEs) play a central role in many image processing tasks. From image denoising to image inpainting, PDE models are ubiquitous. Depending on the specific aims and application at hand, we can often observe a tendency towards higher-order, i.e., mostly fourth-order, PDEs over second-order dynamics. In this talk we will discuss the differences and advantages of both second- and fourth-order imaging approaches in the context of image inpainting, image denoising and image reconstruction for medical imaging applications. The talk will conclude with the proposal of a new model which aims to combine the dynamics of both classes and its analysis in terms of existence and uniqueness of solutions.

This talk is part of the Probabilistic Systems, Information, and Inference Group Seminars series.

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