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Unsupervised linear spectral mixture analysis with AVIRIS data
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作者 谷延锋 杨冬云 张晔 《Journal of Harbin Institute of Technology(New Series)》 EI CAS 2005年第5期471-476,共6页
A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction (MNF) transformation and independent component analysis (ICA). The modified MNF transf... A new algorithm for unsupervised hyperspectral data unmixing is investigated, which includes a modified minimum noise fraction (MNF) transformation and independent component analysis (ICA). The modified MNF transformation is used to reduce noise and remove correlation between neighboring bands. Then the ICA is applied to unmix hyperspectral images, and independent endmembers are obtained from unmixed images by using post-processing which includes image segmentation based on statistical histograms and morphological operations. The experimental results demonstrate that this algorithm can identify endmembers resident in mixed pixels. Meanwhile, the results show the high computational efficiency of the modified MNF transformation. The time consumed by the modified method is almost one fifth of the traditional MNF transformation. 展开更多
关键词 spectral mixture analysis minimum noise fraction independent component analysis linear mixture model adaptive subspace decomposition
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Lithological Discrimination of the Mafic-Ultramafic Complex, Huitongshan, Beishan, China: Using ASTER Data 被引量:8
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作者 Lei Liu Jun Zhou +2 位作者 Dong Jiang Dafang Zhuang Lamin R Mansaray 《Journal of Earth Science》 SCIE CAS CSCD 2014年第3期529-536,共8页
The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusion... The Beishan area has more than seventy mafic-ultramafic complexes sparsely distributed in the area and is of a big potential in mineral resources related to mafic-ultramafic intrusions. Many mafic-ultramafic intrusions which are mostly in small sizes have been omitted by previous works. This research takes Huitongshan as the study area, which is a major district for mafic-ultramafic occurrences in Beishan. Advanced spaceborne thermal emission and reflection radiometer(ASTER) data have been processed and interpreted for mapping the mafic-ultramafic complex. ASTER data were processed by different techniques that were selected based on image reflectance and laboratory emissivity spectra. The visible near-infrared(VNIR) and short wave infrared(SWIR) data were transformed using band ratios and minimum noise fraction(MNF), while the thermal infrared(TIR) data were processed using mafic index(MI) and principal components analysis(PCA). ASTER band ratios(6/8, 5/4, 2/1) in RGB image and MNF(1, 2, 4) in RGB image were powerful in distinguishing the subtle differences between the various rock units. PCA applied to all five bands of ASTER TIR imagery highlighted marked differences among the mafic rock units and was more effective than the MI in differentiating mafic-ultramafic rocks. Our results were consistent with information derived from local geological maps. Based on the remote sensing results and field inspection, eleven gabbroic intrusions and a pyroxenite occurrence were recognized for the first time. A new geologic map of the Huitongshan area was created by integrating the results of remote sensing, previous geological maps and field inspection. It is concluded that the workflow of ASTER image processing, interpretation and ground inspection has great potential for mafic-ultramafic rocks identifying and relevant mineral targeting in the sparsely vegetated arid region of northwestern China. 展开更多
关键词 mafic-ultramafic complex ASTER data band ratio minimum noise fraction mafic index principal component analysis.
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