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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.
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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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Proceedings ArticleDOI

Performance Analysis on Interpolation-based Methods for Fingerprint Images

TL;DR: In this article , the most commonly known interpolation methods namely; nearest neighbor, bilinear, bicubic, and Lanczos interpolations were compared to super resolve fingerprint images and compared the performance of each interpolation method.
Proceedings ArticleDOI

AMSNet: Attention-based Multi-Scale Network for Image SR Reconstruction

TL;DR: AMSNet as mentioned in this paper proposes an attention-based multi-scale super-resolution network (AMSNet), which uses cascaded residual blocks (CRB) to extract image features and Squeeze-and-excitation-based residual upsampling block (SERUB) is designed to enhance important features.
Proceedings ArticleDOI

SLIC Based Digital Image Enlargement

TL;DR: This paper proposes a novel approach to mitigate the color bleeding by segmenting the homogeneous color regions of the image using Simple Linear Iterative Clustering (SLIC) and applying a higher order interpolation technique separately on the isolated segments.

Thermographic image super-resolution based on neural networks

TL;DR: This work studies three neural networks architectures based on deep learning capable of performing super-resolution of RGB images at x2 and x4 scales: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network (SRGAN), Enhanced Deep Residual Networks for Single image Super- Resolution (EDSR), and Wide Activation for Efficient and Accurate Image super-resolution (WDSR).
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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