Lossy compression of hyperspectral images by using Enhanced Multivariance Products Representation (EMPR) method

Sukhanov A., Tuna S., Töreyin B. U.

24th Signal Processing and Communication Application Conference (SIU), Zonguldak, Turkey, 16 - 19 May 2016, pp.1925-1928 identifier

  • Publication Type: Conference Paper / Full Text
  • City: Zonguldak
  • Country: Turkey
  • Page Numbers: pp.1925-1928
  • Keywords: Hyperspectral Image, Enhanced Multivariance Products Representation, Haar Wavelet, Decomposition, Compression
  • Istanbul Technical University Affiliated: Yes


In preceding paper, a compression algorithm for hyperspectral images using a novel multivariate data decomposition method called Enhanced Multivariance Products Representation (EMPR) is developed. The test results obtained by performing some EMPR approximations of different orders and their qualities are reported. In order to improve performance, EMPR approach is applied to high-subband of hyperspectral data which is spectrally decorrelated using Haar wavelet transform. Low subbands are losslessly compressed using JPEG2000 Proposed methods are tested with AVIRIS data, promising compression vs. Peak-Signal-to-Noise Ratios (PSNR) are obtained.