Edge focused super-resolution of thermal images - Archive ouverte HAL Access content directly
Conference Papers Year : 2019

Edge focused super-resolution of thermal images

Abstract

In this work, a super-resolution method is proposed for indoor scenes captured by low-resolution thermal cameras. The proposed method is called Edge Focused Thermal Super-resolution (EFTS) which contains an edge extraction module enforcing the neural networks to focus on the edge of images. Utilizing edge information, our model, based on residual dense blocks, can perform super-resolution for thermal images, while enhancing the visual information of the edges. Experiments on benchmark datasets showed that our EFTS method achieves better performance in comparison to the state-of-the-art techniques.
Fichier principal
Vignette du fichier
Thermal_super_resolution_IJCNN.pdf (2.57 Mo) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-02270646 , version 1 (26-08-2019)

Identifiers

Cite

Yannick Zoetgnande, Jean-Louis Dillenseger, Javad Alirezaie. Edge focused super-resolution of thermal images. International Joint Conference on Neural Networks, Jul 2019, Budapest, Hungary. pp.1-8, ⟨10.1109/IJCNN.2019.8852320⟩. ⟨hal-02270646⟩
83 View
319 Download

Altmetric

Share

Gmail Mastodon Facebook X LinkedIn More