# Image restoration with generalized Gaussian mixture model patch priors

@article{Deledalle2018ImageRW, title={Image restoration with generalized Gaussian mixture model patch priors}, author={Charles-Alban Deledalle and Shibin Parameswaran and Truong Q. Nguyen}, journal={ArXiv}, year={2018}, volume={abs/1802.01458} }

Patch priors have became an important component of image restoration. A powerful approach in this category of restoration algorithms is the popular Expected Patch Log-likelihood (EPLL) algorithm. EPLL uses a Gaussian mixture model (GMM) prior learned on clean image patches as a way to regularize degraded patches. In this paper, we show that a generalized Gaussian mixture model (GGMM) captures the underlying distribution of patches better than a GMM. Even though GGMM is a powerful prior to…

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