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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Test-time augmentation with uncertainty estimation for deep learning-based medical image segmentation
TL;DR: Experiments with segmentation of fetal brains and brain tumors from 2D and 3D Magnetic Resonance Images showed that the test-time augmentation outperforms a single-prediction baseline and dropoutbased multiple predictions, and provides a better uncertainty estimation than calculating the model-based uncertainty alone and helps to reduce overconfident incorrect predictions.
Journal ArticleDOI
A new multiframe super-resolution based on nonlinear registration and a spatially weighted regularization
TL;DR: The hyperelastic image registration model is used to handle the subpixel errors between the unregistered images, while the spatially weighted second order regularization allows to increase the robustness of the restoration step with respect to degradation factors.
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Evaluating Robustness of Deep Image Super-Resolution against Adversarial Attacks.
TL;DR: This paper investigates the robustness of deep learning-based super-resolution methods against adversarial attacks, which can significantly deteriorate the super-resolved images without noticeable distortion in the attacked low-resolution images.
Journal ArticleDOI
Multi-Frame Super-Resolution Reconstruction Based on Gradient Vector Flow Hybrid Field
TL;DR: A novel multi-frame super-resolution (SR) method developed by considering image enhancement and denoising into the SR processing can effectively suppress both Gaussian and salt-and-pepper noise, meanwhile enhance edges of the reconstructed image.
Journal ArticleDOI
Super-resolution imaging and field of view extension using a single camera with Risley prisms.
TL;DR: A novel imaging method using Risley prisms is proposed to achieve super-resolution imaging and field of view (FOV) extension, providing a promising approach for super- resolution reconstruction, large FOV imaging, and foveated imaging with low cost and high efficiency.
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.