Compression of hyperspectral data by spatial/spectral discrete cosine transform

Author

Baizert, Piotr ; Pickering, Mark R. ; Ryan, Michael J.

Author_Institution

Sch. of Electr. Eng., Australian Defence Force Acad., Canberra, ACT, Australia

Volume

4

fYear

2001

fDate

2001

Firstpage

1859

Abstract

The preferred vector quantization technique for the lossless compression of hyperspectral data has been demonstrated to be a combination of mean-normalised vector quantization (M-NVQ) in the spatial domain and the discrete cosine transform (DCT) techniques in the spectral domain. Results for a spatial M-NVQ/spectral DCT coder are between 1.5 and 2.5 times better than the compression ratios obtained by the M-NVQ technique alone. This work shows that, for low distortion levels, further improvements in compression ratio (approximately 0.5 bits/pixel) can be obtained by replacing the spatial M-NVQ technique with the two-dimensional DCT

Keywords

discrete cosine transforms; geophysical signal processing; remote sensing; transform coding; vector quantisation; DCT; M-NVQ; M-NVQ/spectral DCT coder; distortion levels; hyperspectral data; lossless compression; mean normalised vector quantization; spatial domain; spatial/spectral discrete cosine transform; spectral domain; two-dimensional DCT; vector quantization technique; Australia; Discrete cosine transforms; Distortion measurement; Drives; Hyperspectral imaging; Image coding; Image reconstruction; Loss measurement; Pixel; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.977096

Filename

977096