| Abstract: |
| In this talk, we show the most recent techniques in image processing. In particular, we use wavelets as tools to define constraints and variational functionals as measures of complexity of signals. More in general, these techniques are often hybrid methods that combine multiresolution analysis and calculus of variations. On one hand, a relevant advantage in these hybrid techniques is given by the sparsity of the wavelet representation, which directly leads us to study the compression image in terms of approximation error. On the other hand, calculus of variations allows us to improve the process of image denoising. |
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