CERES
CERES TEST Only!
  • Communities & Collections
  • Browse CERES
  • Library Staff Log In
    New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Mei, Jianqiang"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    ItemOpen Access
    Infer thermal information from visual information: a cross imaging modality edge learning (CIMEL) framework
    (MDPI, 2021-11-10) Wang, Shuozhi; Mei, Jianqiang; Yang, Lichao; Zhao, Yifan
    The measurement accuracy and reliability of thermography is largely limited by a relatively low spatial-resolution of infrared (IR) cameras in comparison to digital cameras. Using a high-end IR camera to achieve high spatial-resolution can be costly or sometimes infeasible due to the high sample rate required. Therefore, there is a strong demand to improve the quality of IR images, particularly on edges, without upgrading the hardware in the context of surveillance and industrial inspection systems. This paper proposes a novel Conditional Generative Adversarial Networks (CGAN)-based framework to enhance IR edges by learning high-frequency features from corresponding visual images. A dual-discriminator, focusing on edge and content/background, is introduced to guide the cross imaging modality learning procedure of the U-Net generator in high and low frequencies respectively. Results demonstrate that the proposed framework can effectively enhance barely visible edges in IR images without introducing artefacts, meanwhile the content information is well preserved. Different from most similar studies, this method only requires IR images for testing, which will increase the applicability of some scenarios where only one imaging modality is available, such as active thermography

Quick Links

  • About our Libraries
  • Cranfield Research Support
  • Cranfield University

Useful Links

  • Accessibility Statement
  • CERES Takedown Policy

Contacts-TwitterFacebookInstagramBlogs

Cranfield Campus
Cranfield, MK43 0AL
United Kingdom
T: +44 (0) 1234 750111
  • Cranfield University at Shrivenham
  • Shrivenham, SN6 8LA
  • United Kingdom
  • Email us: researchsupport@cranfield.ac.uk for REF Compliance or Open Access queries

Cranfield University copyright © 2002-2025
Cookie settings | Privacy policy | End User Agreement | Send Feedback