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Multifractal Analysis of Multivariate Images Using Gamma Markov Random Field Priors

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Academic year: 2021

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Figure 1. Illustration of multivariate image scenario (left). Spatial (red) and spectral (blue) components of the proposed bipartite conditional independence graphs between ˜ C 2 i and Z i (right).
Figure 2. Estimation results for a temporal sequence of heterogeneous MRWs decomposed into 50 × 50 × 50 patches of size 2 6 × 2 6 : Prescribed c 2 masks (a); estimates ˆc 2 for two different slices and overall histograms (b); classification labels obtained
Figure 3. Estimation performance for heterogeneous 2D MRWs: Mean (first row), standard deviation (second row), and root-mean square error (third row) in (a) spatial direction x 1 (t = 10, x 2 = 25) and (b) temporal direction t (x 1 = 25, x 2 = 25).
Figure 4. Multifractal analysis of a hyperspectral image (bands 80–160) from the Madonna project.
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