Satellite Data Compression

1. Front Matter

   Pages i-ix

   PDF

2. Development of On-Board Data Compression Technology at Canadian Space Agency

   • Shen-En Qian

   Pages 1-28

3. CNES Studies for On-Board Compression of High-Resolution Satellite Images

   • Carole Thiebaut, Roberto Camarero

   Pages 29-46

4. Low-Complexity Approaches for Lossless and Near-Lossless Hyperspectral Image Compression

   • Andrea Abrardo, Mauro Barni, Andrea Bertoli, Raoul Grimoldi, Enrico Magli, Raffaele Vitulli

   Pages 47-65

5. FPGA Design of Listless SPIHT for Onboard Image Compression

   • Yunsong Li, Juan Song, Chengke Wu, Kai Liu, Jie Lei, Keyan Wang

   Pages 67-85

6. Outlier-Resilient Entropy Coding

   • Jordi Portell, Alberto G. Villafranca, Enrique García-Berro

   Pages 87-113

7. Quality Issues for Compression of Hyperspectral Imagery Through Spectrally Adaptive DPCM

   • Bruno Aiazzi, Luciano Alparone, Stefano Baronti

   Pages 115-147

8. Ultraspectral Sounder Data Compression by the Prediction-Based Lower Triangular Transform

   • Shih-Chieh Wei, Bormin Huang

   Pages 149-168

9. Lookup-Table Based Hyperspectral Data Compression

   • Jarno Mielikainen

   Pages 169-184

10. Multiplierless Reversible Integer TDLT/KLT for Lossy-to-Lossless Hyperspectral Image Compression

    • Jiaji Wu, Lei Wang, Yong Fang, L. C. Jiao

    Pages 185-213

11. Divide-and-Conquer Decorrelation for Hyperspectral Data Compression

    • Ian Blanes, Joan Serra-Sagristà, Peter Schelkens

    Pages 215-232

12. Hyperspectral Image Compression Using Segmented Principal Component Analysis

    • Wei Zhu, Qian Du, James E. Fowler

    Pages 233-251

13. Fast Precomputed Vector Quantization with Optimal Bit Allocation for Lossless Compression of Ultraspectral Sounder Data

    • Bormin Huang

    Pages 253-267

14. Effects of Lossy Compression on Hyperspectral Classification

    • Chulhee Lee, Sangwook Lee, Jonghwa Lee

    Pages 269-285

15. Projection Pursuit-Based Dimensionality Reduction for Hyperspectral Analysis

    • Haleh Safavi, Chein-I Chang, Antonio J. Plaza

    Pages 287-309

Satellite Data Compression covers recent progress in compression techniques for multispectral, hyperspectral and ultra spectral data. A survey of recent advances in the fields of satellite communications, remote sensing and geographical information systems is included. Satellite Data Compression, contributed by leaders in this field, is the first book available on satellite data compression. It covers onboard compression methodology and hardware developments in several space agencies. Case studies are presented on recent advances in satellite data compression techniques via various prediction-based, lookup-table-based, transform-based, clustering-based, and projection-based approaches. This book provides valuable information on state-of-the-art satellite data compression technologies for professionals and students who are interested in this topic. Satellite Data Compression is designed for a professional audience comprised of computer scientists working in satellite communications, sensor system design, remote sensing, data receiving, airborne imaging and geographical information systems (GIS). Advanced-level students and academic researchers will also benefit from this book.

• GIS
• data compression
• geographic information systems
• satellite communications
• satellite data compression
• sensing

• , Space Science and Engineering Center, University of Wisconsin - Madison, Madison, USA

  Bormin Huang

Policies and ethics