Generating infrared image from visible image using Generative Adversarial Networks

Lei An, Jiajia Zhao, Huijun Di

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training deep learning algorithms in unmanned systems. However, how to obtain a large number of infrared images makes it possible to train deep learning algorithm, which is the focus of our attention. In contrast to difficulties in direct shooting, computer simulations can generate large infrared images from visible images. But models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real infrared images, we exploit recent advances in paired image-to-image translation. We extend Pixel2Pixel to generate infrared image from visible image and propose a novel way of multilayer semantic information fusion, which significantly improves the quality of generated images. Finally, the image generated by our proposed PixelPro network is almost consistent with the real image distribution, achieved the purpose of expanding the dataset.

Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages157-161
Number of pages5
ISBN (Electronic)9781728137926
DOIs
Publication statusPublished - Oct 2019
Event2019 IEEE International Conference on Unmanned Systems, ICUS 2019 - Beijing, China
Duration: 17 Oct 201919 Oct 2019

Publication series

NameProceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019

Conference

Conference2019 IEEE International Conference on Unmanned Systems, ICUS 2019
Country/TerritoryChina
CityBeijing
Period17/10/1919/10/19

Keywords

  • Generative Adversarial Networks
  • Image Translation
  • Infrared image

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An, L., Zhao, J., & Di, H. (2019). Generating infrared image from visible image using Generative Adversarial Networks. In Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019 (pp. 157-161). Article 8995962 (Proceedings of the 2019 IEEE International Conference on Unmanned Systems, ICUS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICUS48101.2019.8995962