Journal ArticleDOI
Sparse representation-based MRI super-resolution reconstruction
TLDR
A novel dictionary training method for sparse reconstruction for enhancing the similarity of sparse representations between the low resolution and high resolution MRI block pairs through simultaneous training two dictionaries.About:
This article is published in Measurement.The article was published on 2014-01-01. It has received 73 citations till now. The article focuses on the topics: Real-time MRI & Sparse approximation.read more
Citations
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Journal ArticleDOI
Deep learning methods in real-time image super-resolution: a survey
TL;DR: This paper provides a general overview on background technologies and pays special attention to super-resolution methods built on deep learning architectures for real-time super- resolution, which not only produce desirable reconstruction results, but also enlarge possible application scenarios of super resolution to systems like cell phones, drones, and embedding systems.
Book ChapterDOI
Bayesian Image Quality Transfer
Ryutaro Tanno,Ryutaro Tanno,Aurobrata Ghosh,Francesco Grussu,Enrico Kaden,Antonio Criminisi,Daniel C. Alexander +6 more
TL;DR: A general Bayesian extension of IQT is presented which enables efficient and accurate quantification of uncertainty, providing users with an essential prediction of the accuracy of enhanced images.
Journal ArticleDOI
A trusted medical image super-resolution method based on feedback adaptive weighted dense network.
TL;DR: Experimental results demonstrate that the proposed FAWDN outperforms the state-of-the-art image SR methods and can obtain more clear and trusted medical images than comparative methods.
Journal ArticleDOI
Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization.
TL;DR: Quantitative evaluations show that the SISR framework can generalize well on unseen data collected from other patient tissue cohorts by incorporating the color normalization method, and proposes a self-supervised colornormalization method that can remove staining variation artifacts.
Journal ArticleDOI
Super-Resolution Reconstruction for Two- and Three-Dimensional LA-ICP-MS Bioimaging
TL;DR: This work presents a su-per-resolution reconstruction method for LA-ICP-MS imaging by ablating consecutive layers of a biological specimen with offset orthogonal scans, resulting in a 10x improvement in resolution for quantitative measurement of dystrophin in murine muscle fibres.
References
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Journal ArticleDOI
$rm K$ -SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
TL;DR: A novel algorithm for adapting dictionaries in order to achieve sparse signal representations, the K-SVD algorithm, an iterative method that alternates between sparse coding of the examples based on the current dictionary and a process of updating the dictionary atoms to better fit the data.
Journal ArticleDOI
Image Super-Resolution Via Sparse Representation
TL;DR: This paper presents a new approach to single-image superresolution, based upon sparse signal representation, which generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods.
Book ChapterDOI
On single image scale-up using sparse-representations
TL;DR: This paper deals with the single image scale-up problem using sparse-representation modeling, and assumes a local Sparse-Land model on image patches, serving as regularization, to recover an original image from its blurred and down-scaled noisy version.
Proceedings ArticleDOI
Super-resolution through neighbor embedding
TL;DR: This paper proposes a novel method for solving single-image super-resolution problems, given a low-resolution image as input, and recovers its high-resolution counterpart using a set of training examples, inspired by recent manifold teaming methods.
Journal ArticleDOI
Dictionaries for Sparse Representation Modeling
TL;DR: This paper surveys the various options such training has to offer, up to the most recent contributions and structures of the MOD, the K-SVD, the Generalized PCA and others.