Image Separation With Side Information: A Connected Auto-Encoders Based Approach-Reference-Cited by-同舟云学术

Image Separation With Side Information: A Connected Auto-Encoders Based Approach

Published:2023 Issue: Volume:32 Page:2931-2946
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Pu Wei¹^ORCID,Sober Barak²,Daly Nathan³^ORCID,Zhou Chao¹^ORCID,Sabetsarvestani Zahra⁴,Higgitt Catherine³^ORCID,Daubechies Ingrid⁵,Rodrigues Miguel R. D.¹^ORCID

Affiliation:

1. Department of Electronic and Electrical Engineering, University College London, London, U.K

2. Department of Mathematics and Rhodes Information Initiative, Duke University, Durham, USA

3. Scientific Department, The National Gallery, London, U.K

4. American International Group, London, U.K

5. Department of Electrical and Computer Engineering, Department of Mathematics, Rhodes Information Initiative, Duke University, Durham, USA

Funder

Engineering and Physical Sciences Research Council

Royal Society

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10129219.pdf?arnumber=10129219

Reference64 articles.

1. Advances in multispectral and hyperspectral imaging for archaeology and art conservation

2. Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing;monga;arXiv 1912 10557,2019

3. Visible and infrared imaging spectroscopy of paintings and improved reflectography

4. A Connected Auto-Encoders Based Approach for Image Separation with Side Information: With Applications to Art Investigation

5. Examination of historical paintings by state-of-the-art hyperspectral imaging methods: from scanning infra-red spectroscopy to computed X-ray laminography