| 基于FastICA的高光谱图像压缩技术 |
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| 引用本文： | 辛勤,粘永健,万建伟,何密. 基于FastICA的高光谱图像压缩技术[J]. 电子科技大学学报(社会科学版), 2010, 0(5) |
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| 作者姓名： | 辛勤 粘永健 万建伟 何密 |
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| 作者单位： | 国防科技大学电子科学与工程学院; |
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| 基金项目： | 国家自然科学基金(60572135); 部级预研基金 |
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| 摘 要： | 提出了一种基于快速独立分量分析(FastICA)的高光谱图像压缩算法。首先引入虚拟维数算法估计图像中的目标端元个数,进而提取出感兴趣的目标端元矢量,并初始化快速独立分量分析的混合矩阵;利用最小噪声分量变换对原始数据进行降维,从降维后的主分量中提取独立分量;对独立分量进行恒虚警率检测与形态学滤波,实现目标分割。对高光谱图像进行谱间Karhunen-Loeve变换,利用比例位移法对感兴趣目标的小波系数进行提升,最后对各主分量进行最优码率的SPIHT压缩。实验结果表明,该方法在获得较高压缩性能的同时能够有效地保留感兴趣的目标。
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| 关 键 词： | 高光谱图像 独立分量分析 有损压缩 目标检测 |
Compression Technique for Hyperspectral Imagery Based on FastICA |
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| XIN Qin,NIAN Yong-jian,WAN Jian-wei,, HE Mi. Compression Technique for Hyperspectral Imagery Based on FastICA[J]. Journal of University of Electronic Science and Technology of China(Social Sciences Edition), 2010, 0(5) |
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| Authors: | XIN Qin NIAN Yong-jian WAN Jian-wei HE Mi |
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| Affiliation: | XIN Qin,NIAN Yong-jian,WAN Jian-wei,, HE Mi (College of Electronic Science , Engineering,National University of Defense Technology Changsha 410073) |
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| Abstract: | Efficient compression for hyperspectral imagery has been the research focus for the development of remote sensing technique.The small targets information protection during the compression process without any preknowledge should be necessarily considered.This paper presents a new lossy compression method for hyperspectral imagery based on fast independent component analysis(FastICA).Virtual dimensionality is introduced to determine the number of target endmembers.The mixing matrix of FastICA is initialized b... |
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| Keywords: | hyperspectral imagery independent component analysis lossy compression target detection |
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