Neural Augmentation-Based Saturation Restoration for LDR Images of HDR Scenes-Reference-Cited by-同舟云学术

Neural Augmentation-Based Saturation Restoration for LDR Images of HDR Scenes

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zheng Chaobing¹^ORCID,Ying Wenjian²^ORCID,Wu Shiqian¹^ORCID,Li Zhengguo³^ORCID

Affiliation:

1. Institute of Robotics and Intelligent Systems, School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China

2. College of Weapon, Naval University of Engineering, Wuhan, China

3. SRO Department, Institute for Infocomm Research, A*STAR, Fusionopolis, Singapore

Funder

A*STAR Singapore through Robotics Horizontal Technology Coordinating Office

Nature Science Foundation of Hubei Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10216361.pdf?arnumber=10216361

Reference63 articles.

1. Unsupervised Optical Flow Estimation for Differently Exposed Images in LDR Domain

2. Generation of high dynamic range illumination from a single image for the enhancement of undesirably illuminated images

3. Deep High Dynamic Range Imaging with Large Foreground Motions

4. Single image-based ghost-free high dynamic range imaging using local histogram stretching and spatially-adaptive denoising

5. A versatile HDR video production system

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