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Bayesian approach with prior models which enforce sparsity in signal and image processing

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Figure

Figure 1 Sparsity: explicite sparse signals. The signal at the right is sparse, but its derivative (signal at the left) is still more sparse.
Figure 2 Sparsity: sparse signals in a transformed domaine (Fourier or wavelet). First row: signals, second row: Fourier or wavelettransforms.
Figure 4 Sparsity: sparse images in a transformed domain (Fourier or wavelet). First row: images, second row: Fourier or wavelettransforms.
Figure 5 Generalized Gaussian family. The probability density function p(x) is shown in the left and - ln p(x) is shown in the right.
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