Prediction and compression of multi-temporal hyperspectral images using luminance transform Farkli zamanlarda alinan hiperspektral görüntülerin işiklilik dönüşümü ile tahmini ve sikiştirilmasi

KARACA A. C., Gullu M. K.

26th IEEE Signal Processing and Communications Applications Conference, SIU 2018, İzmir, Turkey, 2 - 05 May 2018, pp.1-4 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2018.8404753
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.1-4
  • Keywords: Hyperspectral imaging, Image compression, Luminance transform, Temporal correlation
  • Yıldız Technical University Affiliated: No


© 2018 IEEE.Correlations between spatial and spectral neighborhoods are utilized for compression of hyperspectral images. For multiple images taken at different times belonging to the same region, better compression performances can be obtained by exploiting temporal correlation. In this paper, multiple luminance transform based compression method is proposed for multi-temporal hyperspectral images. In the first step of the proposed method, target image is predicted from reference image using a linear transform. In the second step, difference between predicted and target image is compressed using 3D-DCT method. Prediction and compression performances of the proposed method are compared with the methods in the literature in terms of signal-to-noise ratio and entropy.