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Journal ArticleDOI

Image super-resolution

TLDR
This paper aims to provide a review of SR from the perspective of techniques and applications, and especially the main contributions in recent years, and discusses the current obstacles for future research.
About
This article is published in Signal Processing.The article was published on 2016-11-01. It has received 378 citations till now.

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Citations
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Journal ArticleDOI

AI-assisted superresolution cosmological simulations – II. Halo substructures, velocities, and higher order statistics

TL;DR: In this article, a superresolution (SR) model was proposed to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity, from computationally cheap low-resolution cosmological N-body simulations.
Journal ArticleDOI

Binarization of Degraded Document Images Using Convolutional Neural Networks and Wavelet-Based Multichannel Images

TL;DR: This paper proposes the utilization of CNNs to identify foreground pixels using novel input-generated multichannel images and proves competitive performance in comparison with state-of-the-art results using the DIBCO database.
Journal ArticleDOI

SLR: Semi-Coupled Locality Constrained Representation for Very Low Resolution Face Recognition and Super Resolution

TL;DR: A novel semi-coupled dictionary learning scheme is proposed to promote discriminative and representative abilities for face recognition and SR simultaneously by relaxing coupled dictionary learning, thereby overcoming the negative effects of one-to-many mapping.
Journal ArticleDOI

Single-image super-resolution via patch-based and group-based local smoothness modeling

TL;DR: A new model is proposed which utilizes both the patch and the group as the basic units of image modeling, called patch-based and group-based local smoothness modeling (PGLSM), which can recover more fine structures and achieve better results than the competing methods with the scaling factor of 2 and 3.
Journal ArticleDOI

Accurate single image super-resolution using multi-path wide-activated residual network

TL;DR: The proposed MWRN model is able to provide very competitive performance with a relatively small number of parameters, compared with the state-of-the-art methods.
References
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Journal ArticleDOI

Image quality assessment: from error visibility to structural similarity

TL;DR: In this article, a structural similarity index is proposed for image quality assessment based on the degradation of structural information, which can be applied to both subjective ratings and objective methods on a database of images compressed with JPEG and JPEG2000.
Book

Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

TL;DR: It is argued that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas.
Journal ArticleDOI

Regularization and variable selection via the elastic net

TL;DR: It is shown that the elastic net often outperforms the lasso, while enjoying a similar sparsity of representation, and an algorithm called LARS‐EN is proposed for computing elastic net regularization paths efficiently, much like algorithm LARS does for the lamba.
Journal ArticleDOI

Nonlinear total variation based noise removal algorithms

TL;DR: In this article, a constrained optimization type of numerical algorithm for removing noise from images is presented, where the total variation of the image is minimized subject to constraints involving the statistics of the noise.
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