Reduced complexity wavelet-based predictive coding of hyperspectral images for FPGA implementation

Agnieszka C. Miguel, Amanda R. Askew, Alexander Chang, Scott Hauck, Richard E. Ladner, Eve A. Riskin

Research output: Contribution to journalConference articlepeer-review

24 Scopus citations

Abstract

We present an algorithm for lossy compression of hyperspectral images for implementation on field programmable gate arrays (FPGA). To greatly reduce the bit rate required to code images, we use linear prediction between the bands to exploit the large amount of inter-band correlation. The prediction residual is compressed using the Set Partitioning in Hierarchical Trees algorithm. To reduce the complexity of the predictive encoder, we propose a bit plane-synchronized closed loop predictor that does not require full decompression of a previous band at the encoder. The new technique achieves almost the same compression ratio as standard closed loop predictive coding and has a simpler on-board implementation.

Original languageEnglish
Pages (from-to)469-478
Number of pages10
JournalData Compression Conference Proceedings
StatePublished - 2004
EventProceedings - DCC 2004 Data Compression Conference - Snowbird, UT., United States
Duration: 23 Mar 200425 Mar 2004

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