Journal ArticleDOI
Image super-resolution
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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.read more
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A Tool for Super-Resolving Multimodal Clinical MRI.
TL;DR: It is shown on simulated data that the proposed approach outperforms conventional model-based techniques, and on a large hospital dataset of multimodal MRIs that the tool can successfully super-resolve very thick-sliced images.
Proceedings ArticleDOI
Deep Super-Resolution Network for Single Image Super-Resolution with Realistic Degradations
TL;DR: A deep SISR network that works for blur kernels of different sizes, and different noise levels in an unified residualCNN-based denoiser network, which significantly improves a practical CNN-based super-resolver for real applications.
Journal ArticleDOI
Efficient $\ell ^0$ Gradient-Based Super-Resolution for Simplified Image Segmentation
TL;DR: In this article, a variational model for single-image super-resolution based on the assumption that the gradient of the target image is sparse is proposed, which can be used to improve the accuracy of standard segmentation algorithms for applications like QR codes and cell detection and land-cover classification problems.
Journal ArticleDOI
Multi-frame image super-resolution reconstruction based on spatial information weighted fields of experts
TL;DR: The proposed WFoE-based SR reconstruction method can obtain better results than traditional FoE model with respect to preserving image edges and has better peak signal-to-noise ratio and visual verisimilitude compared with some existing SR methods.
Proceedings ArticleDOI
DAVE: Dynamic Adaptive Video Encoding for Real-time Video Streaming Applications
Siqi Huang,Jiang Xie +1 more
TL;DR: In this article, a new real-time video streaming protocol, DAVE (Dynamic Adaptive Video Encoding for Real-Time video streaming applications), is proposed, which uses a reinforcement learning based model to learn the optimal video encoding configuration.
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
Hui Zou,Trevor Hastie +1 more
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.