Deep Mean-Shift Priors for Image Restoration
作者： Paolo Favaro , Matthias Zwicker , Siavash Arjomand Bigdeli , Meiguang Jin
DOI: 10.7892/BORIS.113226
关键词:
摘要: In this paper we introduce a natural image prior that directly represents Gaussian-smoothed version of the distribution. We include our in formulation restoration as Bayes estimator also allows us to solve noise-blind problems. show gradient corresponds mean-shift vector on addition, learn field using denoising autoencoders, and use it descent approach perform risk minimization. demonstrate competitive results for deblurring, super-resolution, demosaicing.
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