光谱学与光谱分析 |
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Interference Hyperspectral Data Compression Based on Spectral Classification and Local DPCM |
TU Xiao-long1,2 , HUANG Min1, Lü Qun-bo1, WANG Jian-wei1,2, PEI Lin-lin1,2 |
1. Academy of Opto-Electronics,Chinese Academy of Sciences, Beijing 100094, China 2. University of Chinese Academy of Sciences, Beijing 100049, China |
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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.
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Received: 2012-09-17
Accepted: 2012-11-28
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Corresponding Authors:
TU Xiao-long
E-mail: miluo1122@126.com
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[1] Fellgett P. Journal of the Optical Society of America, 1952, 42:872. [2] Lü Qun-bo, YUAN Yan, XIANGLI Bin(吕群波,袁 艳,相里斌). Acta Photonica Sinica(光子学报),2008,37(3):573. [3] WU Xiao-hua, LI Zi-tian, ZHANG Fan(吴小华,李自田,张 帆). Acta Photonica Sinica(光子学报),2005, 34(9):1346. [4] Lü Qun-bo, XIANGLI Bin(吕群波,相里斌). Acta Photonica Sinica(光子学报),2004,33(6):68. [5] Mailhes Corinne, Vermande Paul, Castanie Francis. J. Optics-Nouvlle Revue Optique, 1990, 21(3):121. [6] SHI Da-lian, Lü Qun-bo, CUI Yan, et al(石大莲,吕群波,崔 燕,等). Acta Photonica Sinica(光子学报),2009,38(6):1530. [7] A Ben David, Agustin Ifarraguerri. Applied Optics, 2002, 41(6):1181. [8] WANG Zeng-zhu, LIU Tong-huai, HUANG Lu(王增柱,刘同怀,黄 鲁). Remote Sensing Technology and Application(遥感技术与应用),2001,16(3):148. |
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