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Updated: Mar 22, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
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Reconstructing Face Image from the Thermal Infrared Spectrum to the Visible Spectrum.

Brahmastro Kresnaraman1, Daisuke Deguchi2, Tomokazu Takahashi3

  • 1Graduate School of Information Science, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan. brahmastrok@murase.m.is.nagoya-u.ac.jp.

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Summary

This study introduces a two-step method using Canonical Correlation Analysis (CCA) to convert thermal face images to the visible spectrum. This enhances security surveillance by enabling facial recognition in low-light conditions.

Keywords:
canonical correlation analysisface imagereconstructionthermal infrared

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Area of Science:

  • Computer Vision
  • Image Processing
  • Biometrics

Background:

  • Thermal cameras offer superior surveillance in low-light conditions as they do not require illumination.
  • Facial identification from thermal images alone presents significant challenges.
  • Reconstructing visible-spectrum face images from thermal data is crucial for enhanced security and recognition.

Purpose of the Study:

  • To develop a method for reconstructing face images from the thermal spectrum to the visible spectrum.
  • To enable subsequent image processing techniques like facial identification and recognition.
  • To improve the capabilities of security surveillance systems in varied lighting conditions.

Main Methods:

  • A two-step reconstruction approach based on Canonical Correlation Analysis (CCA) was proposed.
  • The method leverages the correlation between thermal infrared and visible spectrum images.
  • The first step processes the entire image, while the second step focuses on image patches.

Main Results:

  • The proposed two-step method achieved satisfying reconstruction results.
  • The method demonstrated superior performance compared to existing approaches in both image quality and recognition accuracy.
  • Successful conversion from thermal to visible spectrum images was demonstrated.

Conclusions:

  • The two-step CCA-based thermal-to-visible reconstruction method is effective for facial image enhancement.
  • This technique significantly improves the potential for facial recognition in low-illumination environments.
  • The approach offers a viable solution for enhancing security surveillance systems.