A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Deep Plug-and-Play Super-Resolution for Arbitrary Blur Kernels
[article]
2019
arXiv
pre-print
Preserved Fulltext
To optimize the new degradation induced energy function, we then derive a plug-and-play algorithm via variable splitting technique, which allows us to plug any super-resolver prior rather than the denoiser ...
In the meanwhile, plug-and-play image restoration has been recognized with high flexibility due to its modular structure for easy plug-in of denoiser priors. ...
It also turns out that we can plug super-resolver prior rather than denoiser prior into the plug-and-play framework. ...
arXiv:1903.12529v1
fatcat:3wgb7l3l7nam5pn3rk4n7zonye
Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
To optimize the new degradation induced energy function, we then derive a plug-and-play algorithm via variable splitting technique, which allows us to plug any super-resolver prior rather than the denoiser ...
prior as a modular part. ...
It also turns out that we can plug super-resolver prior rather than denoiser prior into the plug-and-play framework. ...
doi:10.1109/cvpr.2019.00177
dblp:conf/cvpr/0008Z019
fatcat:m4j4scmnwncfdgkqyokbjq3rdi
Unified Single-Image and Video Super-Resolution via Denoising Algorithms
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
We exploit the Plug-and-Play-Prior framework and the Regularization-by-Denoising (RED) approach that extends it, and show how to use such denoisers in order to handle the SISR and the VSR problems using ...
In this work we suggest a simple and robust super-resolution framework that can be applied to single images and easily extended to video. ...
The Plug-and-Play-Prior (PPP) scheme [27] offers a method to separate the two in a manner that allows us to use prior functions that are already integrated into Gaussian denoising algorithms. ...
arXiv:1810.01938v1
fatcat:cnbptuimcjbw7poqh5ib5hjvmq
Learning Deep CNN Denoiser Prior for Image Restoration
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
To this end, this paper aims to train a set of fast and effective CNN (convolutional neural network) denoisers and integrate them into model-based optimization method to solve other inverse problems. ...
Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e.g ...
We gratefully acknowledge the support from NVIDIA Corporation for providing us the Titan X GPU used in this research. ...
doi:10.1109/cvpr.2017.300
dblp:conf/cvpr/ZhangZGZ17
fatcat:pm25evg7pvhkzita6tjnn2wyku
Learning Deep CNN Denoiser Prior for Image Restoration
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
To this end, this paper aims to train a set of fast and effective CNN (convolutional neural network) denoisers and integrate them into model-based optimization method to solve other inverse problems. ...
Recent works have revealed that, with the aid of variable splitting techniques, denoiser prior can be plugged in as a modular part of model-based optimization methods to solve other inverse problems (e.g ...
We gratefully acknowledge the support from NVIDIA Corporation for providing us the Titan X GPU used in this research. ...
arXiv:1704.03264v1
fatcat:5gec5vbgpbcfvcvp73yg7hmi5m
Deep Model-Based Super-Resolution with Non-uniform Blur
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
To this end, we first propose a fast deep plug-and-play algorithm, based on linearized ADMM splitting techniques, which can solve the super-resolution problem with spatially-varying blur. ...
Single-image super-resolution methods seek to restore a high-resolution image from blurred, subsampled, and noisy measurements. ...
Deep plug-and-play methods can be used to solve a large variety of image resoration tasks such as Gaussian denoising [5] , image deblurring [58] or super-resolution [4] . ...
arXiv:2204.10109v2
fatcat:wbpsfhqptre3ld6agpdjcunyky
Deep Unfolding Network for Image Super-Resolution
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
As a result, the proposed network inherits the flexibility of model-based methods to super-resolve blurry, noisy images for different scale factors via a single model, while maintaining the advantages ...
Specifically, by unfolding the MAP inference via a half-quadratic splitting algorithm, a fixed number of iterations consisting of alternately solving a data subproblem and a prior subproblem can be obtained ...
Acknowledgments: This work was partly supported by the ETH Zürich Fund (OK), a Huawei Technologies Oy (Finland) project, an Amazon AWS grant, and Nvidia. ...
arXiv:2003.10428v1
fatcat:jbnctobc2reujhqcy6dyaypssm
Multi-Resolution Data Fusion for Super Resolution Imaging
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2105.06533v5 fatcat:7yiqsdvfojaqhpt7lph62kz3q4Other Versions
We use MACE to prove that using a mismatched back-projector is equivalent to using a standard back-projector and an appropriately modified prior model. ...
Our approach uses small quantities of unpaired high-resolution data to train a neural network prior model denoiser and then uses the Multi-Agent Consensus Equilibrium (MACE) problem formulation to balance ...
Hampton for assistance in data acquisition and Asif Mehmood for his mentorship. ...
arXiv:2105.06533v6
fatcat:m6dte5ul3zanve2xcdc7zvn4za
The Little Engine that Could: Regularization by Denoising (RED)
[article]
2017
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Recent work has answered this question positively, in the form of the Plug-and-Play Prior (P^3) method, showing that any inverse problem can be handled by sequentially applying image denoising steps. ...
We test this approach and demonstrate state-of-the-art results in the image deblurring and super-resolution problems. ...
We leave this and other possibilities of formulating the regularization with the use of f (x) for future work.
When is Plug-and-Play-Prior = RED ? ...
arXiv:1611.02862v3
fatcat:i6haon6za5dxbmpgkgoyevc57a
Deep Learning on Image Denoising: An overview
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we offer a comparative study of deep techniques in image denoising. ...
Next, we compare the state-of-the-art methods on public denoising datasets in terms of quantitative and qualitative analysis. ...
[262] proposed to use cascaded deblurring and singleimage super-resolution (SISR) networks to recover plug-and-play super-resolution images. ...
arXiv:1912.13171v4
fatcat:4ts2xpivhreptelbgeqhljjiri
The Little Engine That Could: Regularization by Denoising (RED)
2017
SIAM Journal of Imaging Sciences
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The recent work by Venkatakrishnan, Bouman, and Wohlberg provides a positive and tantalizing answer to this question, in the form of the Plug-and-Play Prior (P 3 ) method [30, 31, 32, 33] . ...
Recent work has answered this question positively, in the form of the Plug-and-Play Prior (P 3 ) method, showing that any inverse problem can be handled by sequentially applying image denoising steps. ...
We leave this and other possibilities of formulating the regularization with the use of f (x) for future work.
When is Plug-and-Play-Prior = RED? ...
doi:10.1137/16m1102884
fatcat:axnnnf6szzhidjzeyuhpxze3gi
Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
The data-driven methods have a stronger prior knowledge learning capability for huge data, especially for nonlinear statistical features; however, the interpretability of the networks is poor, and they ...
This paper also gives some new insights into the potential future directions, in terms of both methods and applications. ...
Most of the existing plug-and-play prior based image restoration methods treat the CNN Gaussian denoiser as the prior [11, 22] , and some treat the CNN super-resolver as the prior [12] .
C. ...
arXiv:2108.06073v1
fatcat:vdnabzwvvnbvnllrlvzvvqgolm
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts
2021
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Output of Dcraw Camera's ISP (hi-quality jpeg) Joint demosaick+single-image SR Proposed method Figure 1 : ×4 super-resolution results obtained from a burst of 30 raw images acquired with a handheld Panasonic ...
Lumix GX9 camera at 12800 ISO for the top image and 25600 for the bottom image. ...
Acknowledgments We thank Frédéric Guichard for useful discussions and comments. ...
doi:10.1109/iccv48922.2021.00237
fatcat:dhtqfk5cnveyhfv3z4ahetdaw4
Lucas-Kanade Reloaded: End-to-End Super-Resolution from Raw Image Bursts
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
/learning an image prior (regularizer) well suited to the task. ...
The effectiveness of our approach is demonstrated on synthetic and real image bursts, setting a new state of the art on several benchmarks and delivering excellent qualitative results on real raw bursts ...
We provide a quantitative comparison in Table 1 with the model introduced in [4] , as well as a single-image upsampling baseline based on the ResUNet architecture [48] , which we use as a plug-and-play ...
arXiv:2104.06191v2
fatcat:zehpbseaqvanbcelur4pik32wu
Variational Image Restoration Network
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Extensive experiments demonstrate the superiority of the proposed method on three classical image restoration tasks, including image denoising, image super-resolution and JPEG image deblocking. ...
Secondly, existing DL methods are mostly trained on one pre-assumed degradation process for all of the training image pairs, such as the widely used bicubic downsampling assumption in the image super-resolution ...
IRCNN is a non-blind plug-and-play method which embeds a deep denoiser into the traditional HQS algorithm. ...
arXiv:2008.10796v2
fatcat:dhvssrvlyrg6pobgflvrtbbb4a
« Previous
Showing results 1 — 15 out of 174 results