Related papers: Multivariate Fields of Experts

Multivariate Fields of Experts

URL: http://arxiv.org/abs/2508.06490v1
Date: Fri, 08 Aug 2025 17:58:25 GMT
Title: Multivariate Fields of Experts
Authors: Stanislas Ducotterd, Michael Unser,
Abstract summary: We introduce the multivariate fields of experts, a new framework for the learning of image priors.<n>We demonstrate the effectiveness of our proposal across a range of inverse problems that include image denoising, deblurring, compressed-sensing magnetic-resonance imaging, and computed tomography.
Score: 16.78532039510369
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: We introduce the multivariate fields of experts, a new framework for the learning of image priors. Our model generalizes existing fields of experts methods by incorporating multivariate potential functions constructed via Moreau envelopes of the $\ell_\infty$-norm. We demonstrate the effectiveness of our proposal across a range of inverse problems that include image denoising, deblurring, compressed-sensing magnetic-resonance imaging, and computed tomography. The proposed approach outperforms comparable univariate models and achieves performance close to that of deep-learning-based regularizers while being significantly faster, requiring fewer parameters, and being trained on substantially fewer data. In addition, our model retains a relatively high level of interpretability due to its structured design.

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