An Evaluation Framework and a Benchmark for Multi/Hyperspectral Image Compression

  • Authors:
  • Jonathan Delcourt;Alamin Mansouri;Tadeusz Sliwa;Yvon Voisin

  • Affiliations:
  • University of Burgundy, France;University of Burgundy, France;University of Burgundy, France;University of Burgundy, France

  • Venue:
  • International Journal of Computer Vision and Image Processing
  • Year:
  • 2011

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Abstract

This paper benchmarks three multi/hyperspectral image compression approaches: the classic Multi-2D compression approach and two different implementations of 3D approach Full 3D and Hybrid. All approaches are combined with a spectral PCA decorrelation stage to optimize performance. These three compression approaches are compared within a larger comparison framework than the conventionally used PSNR, which includes eight metrics divided into three families. The comparison is carried out with regard to variations in bitrates, spatial, and spectral dimensions variations of images. The time and memory consumption difference between the three approaches is also discussed. Results of this comparison show the weaknesses and strengths of each approach.