Thermal Infrared Colorization Using Deep Learning

Ciftci O., Ali Akcavol M. A.

8th International Conference on Electrical and Electronics Engineering, ICEEE 2021, Antalya, Türkiye, 9 - 11 Nisan 2021, ss.323-326 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/iceee52452.2021.9415929
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.323-326
  • Anahtar Kelimeler: deep learning, image colorization, thermal infrared image
  • Gazi Üniversitesi Adresli: Evet

Özet

© 2021 IEEE.Day by day the usage of infrared cameras has been increasing in the world. With the increasing use of thermal infrared cameras and images, especially in military, security and medicine, the need for coloring thermal infrared images to visible spectrum has arisen. In this study, a deep based model has been developed to generate visible spectrum images (RGB-Red Green Blue) from thermal infrared (TIR) images. In the proposed model, an autoencoder architecture with skip connections has been used to generate RGB images. KAIST-MS (Korea Advanced Institute of Science and Technology-Multispectral) dataset used for training and test the developed model. The experimental results extensively tested using Peak Signal-to-Noise Ratio (PSNR), Least Absolute Deviations (L1), Root Mean Squared Error (RMSE) and Structural Similarity Index Measure (SSIM).