Visible and Infrared Image Fusion Using Encoder-Decoder Network

Visible and Infrared Image Fusion Using Encoder-Decoder Network

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 p...

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Veröffentlicht in:arXiv.org 2024-12
Hauptverfasser: Ferhat Can Ataman, Akar, Gözde Bozdaği
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Sprache:eng
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Computer Science - Computer Vision and Pattern Recognition
Computer Science - Learning
Computer vision
Encoders-Decoders
Image quality
Infrared analysis
Infrared imagery
Real time
Visible spectrum
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Akar, Gözde Bozdaği
description 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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subjects Computer Science - Computer Vision and Pattern Recognition
Computer Science - Learning
Computer vision
Encoders-Decoders
Image quality
Infrared analysis
Infrared imagery
Real time
Visible spectrum
title Visible and Infrared Image Fusion Using Encoder-Decoder Network
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