COMPRESSION OF HYPERSPECTRAL IMAGES USING LUMINANCE TRANSFORM AND 3D-DCT


Can E., KARACA A. C. , Danisman M., URHAN O., Gullu M. K.

38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 22 - 27 July 2018, pp.5073-5076 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/igarss.2018.8518509
  • City: Valencia
  • Country: Spain
  • Page Numbers: pp.5073-5076
  • Keywords: 3D-DCT, luminance transform, hyperspectral image compression
  • Yıldız Technical University Affiliated: Yes

Abstract

DCT based transform techniques are popular in image compression. In this paper, luminance transform is applied to improve the compression performance of 3-D discrete cosine transform (3D-DCT) in hyperspectral images. The proposed scheme consists of two main steps. Firstly, luminance transform is performed on spectral band groups taking the first band image in a group as the reference. The aim of using luminance transform is to reduce the brightness and contrast difference within spectral band groups. Secondly, compression is performed by 3D-DCT followed by entropy encoding. The performance of the proposed approach is compared to 3D-DCT in terms of signal-to-noise ratio (SNR) and mean spectral angle (MSA). It is observed that applying luminance transform before 3D-DCT provides better results especially at low bit-rates.