KSII Transactions on Internet and Information Systems (TIIS)

  • 제12권5호
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  • Pages.2253-2272
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  • 2018
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  • 1976-7277(pISSN)
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  • 1976-7277(eISSN)
한국인터넷정보학회 (Korean Society for Internet Information)
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Multi-focus Image Fusion using Fully Convolutional Two-stream Network for Visual Sensors

  • 투고 : 2017.05.04
  • 심사 : 2017.11.24
  • 발행 : 2018.05.31
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초록

We propose a deep learning method for multi-focus image fusion. Unlike most existing pixel-level fusion methods, either in spatial domain or in transform domain, our method directly learns an end-to-end fully convolutional two-stream network. The framework maps a pair of different focus images to a clean version, with a chain of convolutional layers, fusion layer and deconvolutional layers. Our deep fusion model has advantages of efficiency and robustness, yet demonstrates state-of-art fusion quality. We explore different parameter settings to achieve trade-offs between performance and speed. Moreover, the experiment results on our training dataset show that our network can achieve good performance with subjective visual perception and objective assessment metrics.

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