Balancing Heterogeneous Image Quality for Improved Cross-Spectral Face Recognition

Balancing Heterogeneous Image Quality for Improved Cross-Spectral Face Recognition

Matching infrared (IR) facial probes against a gallery of visible light faces remains a challenge, especially when combined with cross-distance due to deteriorated quality of the IR data. In this paper, we study the scenario where visible light faces are acquired at a short standoff, while IR faces...

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Bibliographic Details
Main Authors: Zhicheng Cao, Xi Cen, Heng Zhao, Liaojun Pang
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Sensors
Subjects:
cross-spectral face recognition
deblurring
deep learning
denoising
infrared
quality imbalance
Online Access:https://www.mdpi.com/1424-8220/21/7/2322

Internet

https://www.mdpi.com/1424-8220/21/7/2322

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