Low memory block tree coding for hyperspectral images

  • Shrish Bajpai
  • Naimur Rahman Kidwai
  • Harsh Vikram Singh
  • Amit Kumar SinghEmail author


Hyperspectral image sensors are resource constrained and have limited on-board memory. Processing of high volume hyperspectral images pose a challenge to the memory and resources of the sensor. Contemporary wavelet based image compression schemes have intensive memory requirement of which 3D-WBTC have superior coding performance due to through the exploitation of the inter sub-band & intra sub-band redundancy. This paper presents a low memory implementation of 3D-WBTC which is a listless scheme by using the fixed size state memory to keep track of block set partitioning and significance testing of wavelet coefficients of transformed hyperspectral images. Memory access time is significantly reduced due to the elimination of lists that leads to reduced complexity. Simulation results of the proposed scheme shows that proposed coder is fast and have very low memory requirement thereby making it a suitable candidate for implementation in resource constrained hyper spectral image sensor.


Hyperspectral image compression Transform coding Wavelet transform Set partition coding scheme Low memory image coder 



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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Shrish Bajpai
    • 1
  • Naimur Rahman Kidwai
    • 2
  • Harsh Vikram Singh
    • 3
  • Amit Kumar Singh
    • 4
    Email author
  1. 1.Electronics Engineering DepartmentDr. A. P. J. Abdul Kalam Technical UniversityLucknowIndia
  2. 2.Department of ECE, Faculty of EngineeringIntegral UniversityLucknowIndia
  3. 3.Department of Electronics EngineeringKamla Nehru Institute of Technology (KNIT)SultanpurIndia
  4. 4.Department of Computer Science and EngineeringNational Institute of Technology PatnaPatnaIndia

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