Compression of hyperspectral imagery using the 3-D DCT and hybrid DPCM/DCT

Author

Abousleman, Glen P. ; Marcellin, Michael W. ; Hunt, Bobby R.

Author_Institution

Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA

Volume

33

Issue

1

fYear

1995

fDate

1/1/1995 12:00:00 AM

Firstpage

26

Lastpage

34

Abstract

Two systems are presented for compression of hyperspectral imagery which utilize trellis coded quantization (TCQ). Specifically, the first system uses TCQ to encode transform coefficients resulting from the application of an 8×8×8 discrete cosine transform (DCT). The second systems uses DPCM to spectrally decorrelate the data, while a 2D DCT coding scheme is used for spatial decorrelation. Side information and rate allocation strategies are discussed. Entropy-constrained code-books are designed using a modified version of the generalized Lloyd algorithm. These entropy constrained systems achieve compression ratios of greater than 70:1 with average PSNRs of the coded hyperspectral sequences exceeding 40.0 dB

Keywords

correlation methods; data compression; differential pulse code modulation; discrete cosine transforms; geophysical signal processing; image coding; image sequences; quantisation (signal); remote sensing; trellis codes; 3D DCT; 8×8×8 discrete cosine transform; compression; entropy constrained system; entropy-constrained code-books; generalized Lloyd algorithm; hybrid DPCM/DCT; hyperspectral imagery; hyperspectral sequences; rate allocation strategies; side information; spatial decorrelation; spectral decorrelation; transform coefficients; trellis coded quantization; Decorrelation; Discrete cosine transforms; Hyperspectral imaging; Hyperspectral sensors; Image coding; Image sensors; Optical imaging; Quantization; Satellites; Spectroscopy;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.368225

Filename

368225