Multiscale feature fusion deep network for single image dehazing with continuous memory mechanism-Reference-Cited by-同舟云学术

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Multiscale feature fusion deep network for single image dehazing with continuous memory mechanism

Published:2023-09 Issue: Volume:287 Page:171144
ISSN:0030-4026
Container-title:Optik
language:en
Short-container-title:Optik

Author:

Xie Zhihua^ORCID,Li Qiang,Zong Sha,Liu Guodong

Funder

Natural Science Foundation of Jiangxi Province

Graduate Innovative Special Fund Projects of Jiangxi Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference53 articles.

1. Dehazenet: an end-to-end system for single image haze removal;Cai;IEEE Trans. Image Process.,2016

2. H. Zhang, V.M. Patel, Densely connected pyramid dehazing network, in: Proceedings of the IEEE conference on computer vision and pattern recognition, 2018.

3. D. Yang, J. Sun, Proximal dehaze-net: A prior learning-based deep network for single image dehazing, in: Proceedings of the European conference on computer vision (ECCV), 2018.

4. B. Li, X. Peng, Z. Wang et al. Aod-net: all-in-one dehazing network, in: Proceedings of the IEEE international conference on computer vision, 2017.

5. “Pyramid Deep dehazing”: an unsupervised single image dehazing method using deep image prior;Xu;Opt. Laser Technol.,2022

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