AIF-LFNet: All-in-Focus Light Field Super-Resolution Method Considering the Depth-Varying Defocus-Reference-Cited by-同舟云学术

AIF-LFNet: All-in-Focus Light Field Super-Resolution Method Considering the Depth-Varying Defocus

Published:2023-08 Issue:8 Volume:33 Page:3976-3988
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Zhou Shubo¹^ORCID,Hu Liang²,Wang Yunlong³^ORCID,Sun Zhenan³^ORCID,Zhang Kunbo³^ORCID,Jiang Xue-Qin¹^ORCID

Affiliation:

1. Institute of Information Science and Technology, Donghua University, Shanghai, China

2. Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

3. Center for Research on Intelligent Perception and Computing, State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10207864/10018388.pdf?arnumber=10018388

Reference56 articles.

1. Spatial-Angular Interaction for Light Field Image Super-Resolution

2. A Multi-Task Collaborative Network for Light Field Salient Object Detection

3. Dense Semantic Labeling with Atrous Spatial Pyramid Pooling and Decoder for High-Resolution Remote Sensing Imagery

4. Simultaneous whole-animal 3D imaging of neuronal activity using light-field microscopy

5. Wave optics theory and 3-D deconvolution for the light field microscope

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