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Rothschild Lecture: Image Compression with Differential Equations

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VMV - Variational methods and effective algorithms for imaging and vision

Partial differential equations (PDEs) are widely used to model phenomena in nature. In this talk we will see that they also have a high potential to compress digital images.

The idea sounds temptingly simple: We keep only a small amount of the pixels and reconstruct the remaining data with PDE -based interpolation. This gives rise to three interdependent questions:

  1. Which data should be kept?
  2. What are the most useful PDEs?
  3. How can the selected data be encoded efficiently?

Solving these problems requires to combine ideas from different mathematical disciplines such as mathematical modelling, optimisation, interpolation and approximation, and numerical methods for PDEs.

Since the talk is intended for a broad audience, we focus on the main ideas, and no specific knowledge in image processing is required.

This talk is part of the Isaac Newton Institute Seminar Series series.

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