Two-stage compression of hyperspectral images with enhanced classification performance

Chulhee Lee, Sungwook Youn, Eunjae Lee, Taeuk Jeong, Joan Serra-Sagristà

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


Most compression methods for hyperspectral images have been optimized to minimize mean squared errors. However, this kind of compression method may not retain all discriminant information, which is important if hyperspectral images are to be used to distinguish among classes. In this paper, we propose a two-stage compression method for hyperspectral images with encoding residual discriminant information. In the proposed method, we first apply a compression method to hyperspectral images, producing compressed image data. From the compressed image data, we produce reconstructed images. Then we generate residual images by subtracting the reconstructed images from the original images. We also apply a feature extraction method to the original images, which produces a set of feature vectors. By applying these feature vectors to the residual images, we generate discriminant feature images which provide the discriminant information missed by the compression method. In the proposed method, these discriminant feature images are also encoded. Experiments with AVIRIS data show that the proposed method provides better compression efficiency and improved classification accuracy than other compression methods.

Original languageEnglish
Title of host publicationRemotely Sensed Data Compression, Communications, and Processing XII
EditorsChulhee Lee, Bormin Huang, Chein-I Chang
ISBN (Electronic)9781510601154
Publication statusPublished - 2016
EventRemotely Sensed Data Compression, Communications, and Processing XII - Baltimore, United States
Duration: 2016 Apr 202016 Apr 21

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherRemotely Sensed Data Compression, Communications, and Processing XII
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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