Poissonian Hyperspectral Image Denoising without Using Anscombe Transform-Reference-Cited by-同舟云学术

Poissonian Hyperspectral Image Denoising without Using Anscombe Transform

Published:2023-07-16 Issue: Volume: Page:
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Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Wang Yulan¹,Wang Peng²,Zhang Xiwang³,Wang Jue¹,Muller Matthieu⁴

Affiliation:

1. Nanjing University of Aeronautics and Astronautics,College of Electronic and Information Engineering,Nanjing,China,210016

2. Chang'an University,Xi’an Key Laboratory of Territorial Spatial Information,Xi’an,China,710064

3. Henan University,Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education,Kaifeng,China,475001

4. University Grenoble Alpes,CNRS, Grenoble INP, GIPSA-lab,Grenoble,France,38000

Funder

Ministry of Natural Resources

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Henan University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282110.pdf?arnumber=10282110

Reference17 articles.

1. Hyperspectral Image Denoising Using Factor Group Sparsity-Regularized Nonconvex Low-Rank Approximation

2. A New Alternating Minimization Algorithm for Total Variation Image Reconstruction

3. Multiresolution Analysis Pansharpening Based on Variation Factor for Multispectral and Panchromatic Images From Different Times

4. An adaptive spatial-spectral total variation approach for Poisson noise removal in hyperspectral images;mansouri;Signal Image and Video Processing,2015

5. Sparsity-Based Poisson Denoising With Dictionary Learning

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