Joint Groupwise Image Registration and Fusion Based on Bounded Generalized Gaussian Mixture Model-Reference-Cited by-同舟云学术

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Joint Groupwise Image Registration and Fusion Based on Bounded Generalized Gaussian Mixture Model

Published:2021-10-22 Issue: Volume: Page:
ISSN:
Container-title:2021 China Automation Congress (CAC)
language:
Short-container-title:

Author:

Liu Rui¹,Zhu Hao¹,Tang Chunxia¹,Najafabadi Hamid Esmaeili²,De Freitas Allan³

Affiliation:

1. Chongqing University of Posts and Telecommunications,College of Automation,Chongqing,China

2. University of Calgary,Department of Electrical and Computer Engineering,Calgary,Canada

3. University of Pretoria,Department of Electrical, Electronic and Computer Engineering,Pretoria,South Africa

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9727224/9727236/09728237.pdf?arnumber=9728237

Reference20 articles.

1. Groupwise Registration of Multimodal Images by an Efficient Joint Entropy Minimization Scheme

2. Jointly registering and fusing images from multiple sensors

3. A maximum likelihood approach to joint groupwise image registration and fusion by a Student-t mixture model;zhu;2019 22th International Conference on Information Fusion,2019

4. An adaptive Kalman filter with inaccurate noise covariances in the presence of outliers;zhu;IEEE Transactions on Automatic Control,2021

5. Bounded generalized Gaussian mixture model

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