Deep Convolutional Neural Network for Multi-Modal Image Restoration and Fusion

In this paper, we propose a novel deep convolutional neural network to solve the general multi-modal image restoration (MIR) and multi-modal image fusion (MIF) problems. Different from other methods based on deep learning, our network architecture is designed by drawing inspirations from a new propo...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence Vol. 43; no. 10; pp. 3333 - 3348
Main Authors:	Deng, Xin, Dragotti, Pier Luigi
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.10.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Coding Computer architecture Computer vision Convolutional codes Convolutional neural networks Feature extraction Image coding Image fusion Image processing Image reconstruction Image resolution Image restoration Machine learning Modules multi-modal convolutional sparse coding Multi-modal image restoration Neural networks Task analysis
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
Online Access:	Get full text
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