PRNet: Pyramid Restoration Network for RAW Image Super-Resolution-Reference-Cited by-同舟云学术

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PRNet: Pyramid Restoration Network for RAW Image Super-Resolution

Published:2024 Issue: Volume:10 Page:479-495
ISSN:2333-9403
Container-title:IEEE Transactions on Computational Imaging
language:
Short-container-title:IEEE Trans. Comput. Imaging

Author:

Ling Mingyang¹^ORCID,Chang Kan²^ORCID,Huang Mengyuan²^ORCID,Li Hengxin³^ORCID,Dang Shuping⁴^ORCID,Li Baoxin⁵^ORCID

Affiliation:

1. School of Electrical Engineering, Guangxi University, Nanning, China

2. School of Computer and Electronic Information, Guangxi University, Nanning, China

3. Shenzhen Xiaomi Communications Co., Ltd, Shenzhen, China

4. School of Electrical, Electronic and Mechanical Engineering, University of Bristol, Bristol, U.K.

5. Department of Computer Science, Arizona State University, Tempe, AZ, USA

Funder

National Natural Science Foundation of China

Guangxi Key R&D Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6745852/10398876/10463120.pdf?arnumber=10463120

Reference71 articles.

1. Image Super-Resolution Using Deep Convolutional Networks

2. Accelerating the Super-Resolution Convolutional Neural Network

3. Deep Learning for Image Super-Resolution: A Survey

4. Burst photography for high dynamic range and low-light imaging on mobile cameras

5. Deep joint demosaicking and denoising

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1. Enhanced local distribution learning for real image super-resolution;Computer Vision and Image Understanding;2024-10

2. Object detection on low-resolution images with two-stage enhancement;Knowledge-Based Systems;2024-09

3. Joint Image and Feature Enhancement for Object Detection under Adverse Weather Conditions;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. A Two-Stage Enhancement Method for Object Detection on Low-Resolution Images;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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