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.read more
Citations
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Proceedings ArticleDOI
Multi-Frame Super-Resolution: A Survey
Mahmoud Moustafa Khattab,Akram M. Zeki,Ali Amer Alwan,Ahmed Said Badawy,Lalitha Saroja Thota +4 more
TL;DR: A general survey of the available multi-frame super resolution approaches is explained and several image quality metrics are discussed to measure the similarity between the reconstructed image and the original image.
Proceedings ArticleDOI
Evolving imaging model for super-resolution reconstruction
TL;DR: A genetic algorithm is introduced to optimize the SRR hyper-parameters and to discover the actual IM by evolving the kernels exploited in the IM and reported experimental results indicate that this approach outperforms the state of the art for a variety of images, including difficult real-life satellite data.
Journal ArticleDOI
Adaptive lq-norm constrained general nonlocal self-similarity regularizer based sparse representation for single image super-resolution
Jinming Li,Wei Guan +1 more
TL;DR: Wang et al. as discussed by the authors proposed an adaptive lq-norm constrained general nonlocal self-similarity (NLSS) regularizer, which can integrate the advantages of the traditional NLSS prior and the row RL prior and adaptively assign different q values to handle the different image contents.
Book ChapterDOI
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
Shuo Wang,Shuo Wang,Chen Qin,Nicoló Savioli,Chen Chen,Declan P. O'Regan,Stuart A. Cook,Yike Guo,Daniel Rueckert,Wenjia Bai +9 more
TL;DR: In this article, a latent optimisation framework was proposed to jointly perform motion correction and super-resolution for cardiac image segmentation, which alleviated the need of paired low-resolution and high-resolution images for supervised learning.
Journal ArticleDOI
PWNet: An Adaptive Weight Network for the Fusion of Panchromatic and Multispectral Images
TL;DR: The proposed PWNet works by learning adaptive weight maps for different CS-based and MRA-based methods through an end-to-end trainable neural network (NN), which inherits the data adaptability or flexibility of NN, while maintaining the advantages of traditional 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
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.