Name
Abstract | ||
|---|---|---|
In this paper, a new algorithm for lossless compression of hyperspectral images is proposed. The spectral redundancy in hyperspectral images is exploited using a context-match method driven by the correlation between adjacent bands. This method is suitable for hyperspectral images in the band-sequential format. Moreover, this method compares favorably with the recent proposed lossless compression algorithms in terms of compression, with a lower complexity. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TGRS.2007.906085 | IEEE T. Geoscience and Remote Sensing |
Keywords | Field | DocType |
remote sensing,compression algorithms,lossless compression,correlation,entropy coding | Computer science,Theoretical computer science,Redundancy (engineering),Vector quantization,Artificial intelligence,Computer vision,Full spectral imaging,Lossy compression,Pattern recognition,Hyperspectral imaging,Data compression,Image resolution,Lossless compression | Conference |
Volume | Issue | ISSN |
45 | 12 | 0196-2892 |
ISBN | Citations | PageRank |
0-7695-2309-9 | 26 | 1.54 |
References | Authors | |
23 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongqiang Wang | 1 | 26 | 1.54 |
| S. Derin Babacan | 2 | 534 | 26.60 |
| Khalid Sayood | 3 | 868 | 88.12 |