Name
Abstract | ||
|---|---|---|
Hyperspectral sensors have been of a growing interest over the past few decades for Earth observation as well as deep space exploration. However, the amount of data provided by such sensors requires an efficient compression system which is yet to be defined. It is hoped that the particular statistical properties of such images can be used to obtain very efficient compression algorithms.This paper proposes a method to find the most suitable wavelet decomposition for hyperspectral images and introduces the possibility of non isotropic decomposition. The decomposition is made by choosing the decomposition that provides an optimal rate-distortion trade-off. The obtained decomposition exhibits better performances in terms of rate-distortion curves compared to isotropic decomposition for high bitrates as well as for low bitrates. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ICASSP.2006.1660268 | 2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13 |
Keywords | Field | DocType |
statistics,compression algorithms,deep space exploration,earth observation,wavelet transforms,image resolution,compression algorithm,anisotropic magnetoresistance,hyperspectral imaging,space exploration,hyperspectral sensors,earth,remote sensing,image sensors | Isotropy,Image sensor,Pattern recognition,Computer science,Deep space exploration,Hyperspectral imaging,Artificial intelligence,Data compression,Image resolution,Wavelet packet decomposition,Wavelet transform | Conference |
ISSN | Citations | PageRank |
1520-6149 | 5 | 0.54 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emmanuel Christophe | 1 | 166 | 13.83 |
| C. Mailhes | 2 | 88 | 6.45 |
| P. Duhamel | 3 | 146 | 18.79 |