title: [Interference hyperspectral data compression based on spectral classification and local DPCM].
abstract: In order to get a high compression ratio, according to the spatial dimension correlation and the interference spectral dimension correlation of interference hyperspectral image data, the present article provides a new compression algorithm that combines spectral classification with local DPCM. This algorithm requires spectral classification for the whole interference hyperspectral image to get a classification number matrix corresponding to the two-dimensional space and a spectral classification library corresponding to the interference spectra first, then local DPCM is performed for the spectral classification library to get a further compression. As the first step of the compression, the spectral classification is very important to the compression effect. This article analyzes the differences of compression effect with different standard and different accuracy of classification, the relative Euclidean distance standard is better than the angle standard and the interference RQE standard. Finally, this article chooses an appropriate standard of compression and achieves the combined compression algorithm with programming. Compared to JPEG2000, the compression effect of combined compression algorithm is better.
authors.affiliation: Academy of Opto-Electronics, Chinese Academy of Sciences, Beijing 100094, China. miluo1122@126.com
authors.forename: Xiao-Long
authors.initials: XL
authors.lastname: Tu
authors.forename: Min
authors.initials: M
authors.lastname: Huang
authors.forename: Qun-Bo
authors.initials: QB
authors.lastname: Lü
authors.forename: Jian-Wei
authors.initials: JW
authors.lastname: Wang
authors.forename: Lin-Lin
authors.initials: LL
authors.lastname: Pei