A Generative Adversarial Network for Infrared and Visible Image Fusion Based on Semantic Segmentation

This paper proposes a new generative adversarial network for infrared and visible image fusion based on semantic segmentation (SSGAN), which can consider not only the low-level features of infrared and visible images, but also the high-level semantic information. Source images can be divided into fo...

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Detalles Bibliográficos
Autores principales: Hou, Jilei, Zhang, Dazhi, Wu, Wei, Ma, Jiayi, Zhou, Huabing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004063/
https://www.ncbi.nlm.nih.gov/pubmed/33801048
http://dx.doi.org/10.3390/e23030376

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8004063/
https://www.ncbi.nlm.nih.gov/pubmed/33801048
http://dx.doi.org/10.3390/e23030376

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