Title :
The lossless compression of AVIRIS images by vector quantization
Author :
Ryan, Michael J. ; Arnold, John F.
Author_Institution :
Australian Defence Force Acad., Canberra, ACT, Australia
fDate :
5/1/1997 12:00:00 AM
Abstract :
The structure of hyperspectral images reveals spectral responses that would seem ideal candidates for compression by vector quantization. This paper outlines the results of an investigation of lossless vector quantization of 224-band Airborne/Visible Infrared imaging Spectrometer (AVIRIS) images. Various vector formation techniques are identified and suitable quantization parameters are investigated. A new technique, mean-normalized vector quantization (M-NVQ), is proposed which produces compression performances approaching the theoretical minimum compressed image entropy of 5 bits/pixel. Images are compressed from original image entropies of between 8.28 and 10.89 bits/pixel to between 4.83 and 5.90 bits/pixel
Keywords :
geophysical signal processing; geophysical techniques; image coding; image processing; remote sensing; vector quantisation; AVIRIS; Airborne Visible Infrared imaging Spectrometer; IR imaging; M-NVQ; data compression; geophysical measurement technique; hyperspectral image; image processing; land surface; lossless compression; mean-normalized vector quantization; multispectral method; optical imaging; terrain mapping; vector quantization; visible; Entropy; Hyperspectral imaging; Hyperspectral sensors; Image coding; Image sensors; Image storage; Infrared imaging; Pixel; Propagation losses; Vector quantization;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
