Hyperspectral Image Compression Algorithms—A Review

  • K. Subhash Babu
  • V. Ramachandran
  • K. K. Thyagharajan
  • Geeta Santhosh
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 325)


Satellite-based remote sensing applications require collection of high volumes of image data of which hyperspectral images are a particular type. Hyperspectral images are collected by high-resolution instruments over a very large number of wavelengths on board a satellite/airborne vehicle and then sent onwards to a ground station for further processing. Compression of hyperspectral images is undertaken to reduce the on-board memory requirement, communication channel capacity, and the download time. Compression algorithms can be either lossless or lossy. The purpose of this paper is to review a number of compression techniques employed for onsite processing of hyperspectral image data, to reduce the transmission overhead. A review of the theory of hyperspectral images and the compression techniques employed therein with emphasis on recent research developments is presented. Recent research on video compression techniques for hyperspectral imaging (HSI) is also discussed.


Hyperspectral imaging Compression Lossless Lossy 


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Copyright information

© Springer India 2015

Authors and Affiliations

  • K. Subhash Babu
    • 1
  • V. Ramachandran
    • 2
  • K. K. Thyagharajan
    • 3
  • Geeta Santhosh
    • 4
  1. 1.CSE DepartmentJawaharlal Nehru Technological University-KakinadaKakinadaIndia
  2. 2.RMD Engineering CollegeKavaraipettaiIndia
  3. 3.NITDimapurIndia
  4. 4.MCA DepartmentSSN College of Engineering KalavakkamChennaiIndia

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