Joint regularization and low-rank fusion for atmospheric turbulence removal-Reference-Cited by-同舟云学术

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Joint regularization and low-rank fusion for atmospheric turbulence removal

Published:2021-08-06 Issue: Volume: Page:
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Qu Yanyun,Yang Wenjin,Xie Yuan,Wu Weiwei,Wu Yang,Wang Hanzi

Funder

the National Natural Science Foundation of China

the National Key Research and Development Program of China

the Natural Science Foundation of Shanghai

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-021-06336-5.pdf

Reference35 articles.

1. Han M, Lyu Z, Qiu T, Xu M (2018) A review on intelligence dehazing and color restoration for underwater images. IEEE Trans Man Cybern Part A Syst Hum 50:1820–1832

2. Yuan Q, Zhang L, Shen H (2014) Hyperspectral image denoising with a spatial spectral view fusion strategy. IEEE Trans Geosci Remote Sens 52(5):2314–2325

3. Li W, Zhang D, Liu Z, Qiao X (2005) Fast block-based image restoration employing the improved best neighborhood matching approach. IEEE Trans Syst Man Cybern Part A Syst Hum 35(4):546–555

4. Hong J, Cho S, Cho U (2009) A novel evolutionary approach to image enhancement filter design: method and applications. IEEE Trans Syst Man Cybern Part B Cybern 32(11):1446–1457

5. Bue BD, Thompson DR, Eastwood M, Green RO (2015) Real-time atmoshperic correction of AVIRIS-NG imagery. IEEE Trans Geosci Remote Sens 53(12):6419–6428

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