A Maximum Likelihood Approach to Joint Groupwise Image Registration and Fusion by a Student-$t$ Mixture Model-Reference-Cited by-同舟云学术

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A Maximum Likelihood Approach to Joint Groupwise Image Registration and Fusion by a Student-$t$ Mixture Model

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:2019 22th International Conference on Information Fusion (FUSION)
language:
Short-container-title:

Author:

Zhu Hao¹,Tang Chunxia¹,De Freitas Allan²,Mihaylova Lyudmila³

Affiliation:

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

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

3. University of Sheffield,Department of Automatic Control and Systems Engineering,Sheffield,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8977236/9011156/09011410.pdf?arnumber=9011410

Reference20 articles.

1. Ensemble image registration by a spatially constrained clustering approach

2. Likelihood maximization approach to image registration;zhu;IEEE Transactions on Image Processing,2002

3. A Maximum Likelihood Approach to Joint Image Registration and Fusion

4. Joint Image Registration and Fusion for Panchromatic and Multispectral Images

5. Jointly registering and fusing images from multiple sensors

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