DenseFuse: A Fusion Approach to Infrared and Visible Images

In this paper, we present a novel deep learning architecture for infrared and visible images fusion problems. In contrast to conventional convolutional networks, our encoding network is combined with convolutional layers, a fusion layer, and dense block in which the output of each layer is connected...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 28; H. 5; S. 2614 - 2623
Hauptverfasser:	Li, Hui, Wu, Xiao-Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.05.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Architecture Artificial neural networks Coding Decoding deep learning dense block Feature extraction Image coding Image contrast Image fusion Image reconstruction infrared image Infrared imagery Machine learning Subjective assessment Training visible image
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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