Frontiers of Information Technology & Electronic Engineering
>> 2020,
Volume 21,
Issue 7
doi:
10.1631/FITEE.1900336
Multi-focus image fusion based on fully convolutional networks
Affiliation(s): Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China; College of Computer Science and Technology, Jilin University, Changchun 130012, China; less
Received: 2019-07-07
Accepted: 2020-07-10
Available online: 2020-07-10
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Abstract
We propose a method, in which a fully convolutional network for focus detection (FD-FCN) is constructed. To obtain more precise focus detection maps, we propose to add s in the network to make both detailed and abstract visual information available when using FD-FCN to generate maps. A new training dataset for the proposed network is constructed based on dataset CIFAR-10. The image fusion algorithm using FD-FCN contains three steps: focus maps are obtained using FD-FCN, decision map generation occurs by applying a morphological process on the focus maps, and image fusion occurs using a decision map. We carry out several sets of experiments, and both subjective and objective assessments demonstrate the superiority of the proposed fusion method to state-of-the-art algorithms.
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