Compression of hyperspectral images using adaptive luminance transform Hiperspektral görüntülerin uyarlamali işiklilik dönüşümü ile sikiştirilmasi

Can E., KARACA A. C., Danisman M., URHAN O., 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.2018.8404763
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.1-4
  • Keywords: 3D-DCT, Correlation matrix, Luminance transform
  • Yıldız Technical University Affiliated: No


© 2018 IEEE.In this paper, compression of hyperspectral images with luminance transform is explained. First, similar image bands are grouped on hyperspectral image and luminance transform is performed independently on these groups. After luminance transform, compression is carried out by using discrete cosine transform (3D-DCT), quantization and entropy coding, for each group. In experimental studies, compression performances are measured using signal-to-noise ratio and bit rates. The proposed method increases signal-to-noise ratio 10 dB at 0.1 bit-per-pixel compared to 3D-DCT based compression.