Visible and Infrared Image Fusion Using Encoder-Decoder Network

• URL: http://arxiv.org/abs/2412.08073v1
• Date: Wed, 11 Dec 2024 03:42:31 GMT
• Title: Visible and Infrared Image Fusion Using Encoder-Decoder Network
• Authors: Ferhat Can Ataman, Gözde Bozdaği Akar,
• Abstract summary: We present a novel learning-based solution to image fusion problem focusing on infrared and visible spectrum images. The proposed solution utilizes only convolution and pooling layers together with a loss function using no-reference quality metrics.
• Score: 0.0
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• Abstract: The aim of multispectral image fusion is to combine object or scene features of images with different spectral characteristics to increase the perceptual quality. In this paper, we present a novel learning-based solution to image fusion problem focusing on infrared and visible spectrum images. The proposed solution utilizes only convolution and pooling layers together with a loss function using no-reference quality metrics. The analysis is performed qualitatively and quantitatively on various datasets. The results show better performance than state-of-the-art methods. Also, the size of our network enables real-time performance on embedded devices. Project codes can be found at \url{https://github.com/ferhatcan/pyFusionSR}.

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