Novel Lossless Compression Method for Hyperspectral Images Based on Variable Forgetting Factor Recursive Least Squares
Changguo Li, Fuquan Zhu, Journal of Information Processing Systems Vol. 20, No. 5, pp. 663-674, Oct. 2024
https://doi.org/10.3745/JIPS.02.0219
Keywords: Causal Neighborhood, Hyperspectral Image, Lossless compression, Variable Forgetting Factor Recursive Least Squares
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Cite this article
[APA Style]
Li, C. & Zhu, F. (2024). Novel Lossless Compression Method for
Hyperspectral Images Based on Variable Forgetting
Factor Recursive Least Squares. Journal of Information Processing Systems, 20(5), 663-674. DOI: 10.3745/JIPS.02.0219.
[IEEE Style]
C. Li and F. Zhu, "Novel Lossless Compression Method for
Hyperspectral Images Based on Variable Forgetting
Factor Recursive Least Squares," Journal of Information Processing Systems, vol. 20, no. 5, pp. 663-674, 2024. DOI: 10.3745/JIPS.02.0219.
[ACM Style]
Changguo Li and Fuquan Zhu. 2024. Novel Lossless Compression Method for
Hyperspectral Images Based on Variable Forgetting
Factor Recursive Least Squares. Journal of Information Processing Systems, 20, 5, (2024), 663-674. DOI: 10.3745/JIPS.02.0219.