
Learning Generic Diffusion Processes for Image Restoration
Image restoration problems are typical illposed problems where the regu...
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Learned Experts' Assessmentbased Reconstruction Network ("LEARN") for Sparsedata CT
Compressive sensing (CS) has proved effective for tomographic reconstruc...
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Speckle Reduction with Trained Nonlinear Diffusion Filtering
Speckle reduction is a prerequisite for many image processing tasks in s...
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Learning Nonlocal Image Diffusion for Image Denoising
Image diffusion plays a fundamental role for the task of image denoising...
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Image Denoising via Multiscale Nonlinear Diffusion Models
Image denoising is a fundamental operation in image processing and holds...
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Poisson Noise Reduction with Higherorder Natural Image Prior Model
Poisson denoising is an essential issue for various imaging applications...
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Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Discriminative model learning for image denoising has been recently attr...
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Fast and Accurate Poisson Denoising with Optimized Nonlinear Diffusion
The degradation of the acquired signal by Poisson noise is a common prob...
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On learning optimized reaction diffusion processes for effective image restoration
For several decades, image restoration remains an active research topic ...
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Higherorder MRFs based image super resolution: why not MAP?
A trainable filterbased higherorder Markov Random Fields (MRFs) model ...
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A higherorder MRF based variational model for multiplicative noise reduction
The Fields of Experts (FoE) image prior model, a filterbased higherord...
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iPiano: Inertial Proximal Algorithm for NonConvex Optimization
In this paper we study an algorithm for solving a minimization problem c...
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A bilevel view of inpainting  based image compression
Inpainting based image compression approaches, especially linear and non...
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Revisiting lossspecific training of filterbased MRFs for image restoration
It is now well known that Markov random fields (MRFs) are particularly e...
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Learning ℓ_1based analysis and synthesis sparsity priors using bilevel optimization
We consider the analysis operator and synthesis dictionary learning prob...
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Insights into analysis operator learning: From patchbased sparse models to higherorder MRFs
This paper addresses a new learning algorithm for the recently introduce...
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