DocumentCode :
297871
Title :
A bounded distortion compression scheme for hyper-spectral image data
Author :
Memon, Nasir D.
Author_Institution :
Dept. of Comput. Sci., Northern Illinois Univ., DeKalb, IL, USA
Volume :
2
fYear :
1996
fDate :
27-31 May 1996
Firstpage :
1039
Abstract :
Presents a new approach for nearly lossless compression of multispectral image data that exploits both spectral and spatial correlations in a simple and adaptive manner. What the authors have described is just one choice of predictor, re-ordering and encoding. A number of alternatives can be used. Implementation results with a few different choices schemes are currently under investigation and will will be described at a later date. Also, the authors need to make more detailed comparisons of compression performances obtained with other lossy and nearly-lossless schemes given in the literature
Keywords :
adaptive signal processing; data compression; geophysical signal processing; geophysical techniques; image coding; linear predictive coding; remote sensing; sensor fusion; adaptive signal processing; bounded distortion compression scheme; encoding; geophysical measurement technique; hyperspectral image data compression; image processing; land surface; lossless compression; multispectral image data; nearly-lossless scheme; predictor; re-ordering; remote sensing; sensor fusion; signal processing; spatial correlation; spectral correlation; terrain mapping; Cause effect analysis; Computer science; Data compression; Entropy; Image analysis; Image coding; Image reconstruction; Performance analysis; Piecewise linear techniques; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International
Conference_Location :
Lincoln, NE
Print_ISBN :
0-7803-3068-4
Type :
conf
DOI :
10.1109/IGARSS.1996.516559
Filename :
516559
Link To Document :
بازگشت