Blind deblurring and denoising via a learning deep CNN denoiser prior and an adaptive L 0 ‐regularised gradient prior for passive millimetre‐wave images-Reference-Cited by-同舟云学术

Blind deblurring and denoising via a learning deep CNN denoiser prior and an adaptive L 0 ‐regularised gradient prior for passive millimetre‐wave images

Published:2020-12 Issue:17 Volume:14 Page:4774-4784
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Sun Dianjun¹²³^ORCID,Shi Yu¹²³,Feng Yayuan¹²³

Affiliation:

1. School of Electrical and Information Engineering, Wuhan Institute of TechnologyWuhanHubei430074People's Republic of China

2. Hubei Key Laboratory of Optical Information and Pattern RecognitionWuhanHubei430074People's Republic of China

3. Hubei Research Center of Video Image and High Definition ProjectionWuhanHubei430074People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2020.1193

Reference34 articles.

1. Passive millimeter‐wave imaging;Yujiri L.;IEEE Microw. Mag.,2003

2. Parametric blind deconvolution for passive millimeter wave images with framelet regularization;Fang F.;Optik.,2014

3. Passive millimeter‐wave imaging with superresolution;Pirogov Y.;SPIE. Image Signal Process. Remote Sens. X.,2004

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