research-article

CNN-based Image Super-Resolution and Deblurring

Authors:

Jie RenAuthors Info & Claims

VSIP '19: Proceedings of the 2019 International Conference on Video, Signal and Image Processing

Pages 70 - 74

https://doi.org/10.1145/3369318.3369328

Published: 10 January 2020 Publication History

Abstract

Image super-resolution and deblurring are two highly ill-posed problems that are usually dealt separately. However, real-world images are often low-resolution and have complex blurring. In this paper, non-uniform motion blur and super-resolution task are combined to reconstruct a clear high-resolution image directly from the blurred low-resolution input. We propose a two-branch network based on convolutional neural network(CNN) to reconstruct images, which mainly include super-resolution module and deblurring module. In addition, we use novel loss functions to generate more realistic images. Experimental results show that the method proposed in this paper can reconstruct sharper high-resolution images than other state-of-the-art algorithms, and the proposed model is lightweight, requiring a low computational cost.

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Cited By

Xie PHe JSong CXue M(2024)A Novel Encoder-Decoder Network with Multi-domain Information Fusion for Video DeblurringPattern Recognition10.1007/978-3-031-78125-4_11(152-166)Online publication date: 5-Dec-2024
https://doi.org/10.1007/978-3-031-78125-4_11
Neji HHalima MNogueras-Iso JHamdani TQahtani AAlmutiry ODhahri HAlimi A(2023)Deep architecture for super-resolution and deblurring of text imagesMultimedia Tools and Applications10.1007/s11042-023-15340-x83:2(3945-3961)Online publication date: 20-May-2023
https://doi.org/10.1007/s11042-023-15340-x
Batchuluun GKang JNguyen DPham TArsalan MPark K(2021)Deep Learning-Based Thermal Image Reconstruction and Object DetectionIEEE Access10.1109/ACCESS.2020.30484379(5951-5971)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2020.3048437
Show More Cited By

Index Terms

CNN-based Image Super-Resolution and Deblurring
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Reconstruction
  2. Computer graphics
    1. Image manipulation
      1. Image processing

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cover image ACM Other conferences

VSIP '19: Proceedings of the 2019 International Conference on Video, Signal and Image Processing

October 2019

135 pages

ISBN:9781450371483

DOI:10.1145/3369318

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UNAM: Universidad Nacional Autonoma de Mexico
Wuhan Univ.: Wuhan University, China
NWPU: Northwestern Polytechnical University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2020

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VSIP 2019

VSIP 2019: 2019 International Conference on Video, Signal and Image Processing

October 29 - 31, 2019

Wuhan, China

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Cited By

Xie PHe JSong CXue M(2024)A Novel Encoder-Decoder Network with Multi-domain Information Fusion for Video DeblurringPattern Recognition10.1007/978-3-031-78125-4_11(152-166)Online publication date: 5-Dec-2024
https://doi.org/10.1007/978-3-031-78125-4_11
Neji HHalima MNogueras-Iso JHamdani TQahtani AAlmutiry ODhahri HAlimi A(2023)Deep architecture for super-resolution and deblurring of text imagesMultimedia Tools and Applications10.1007/s11042-023-15340-x83:2(3945-3961)Online publication date: 20-May-2023
https://doi.org/10.1007/s11042-023-15340-x
Batchuluun GKang JNguyen DPham TArsalan MPark K(2021)Deep Learning-Based Thermal Image Reconstruction and Object DetectionIEEE Access10.1109/ACCESS.2020.30484379(5951-5971)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2020.3048437
Batchuluun GLee YNguyen DPham TPark K(2020)Thermal Image Reconstruction Using Deep LearningIEEE Access10.1109/ACCESS.2020.30078968(126839-126858)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3007896

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