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題名:Adaptive Filtering Approaches to Multispectral Image Classification
書刊名:航測及遙測學刊
作者:張麗娜倪富荃
作者(外文):Chang, LenaNi, Fu-chuan
出版日期:2007
卷期:12:4
頁次:頁343-351
主題關鍵詞:多頻帶影像影像分類適應性信號子空間投影法埃根特徵類神經網路Multispectral imageImage classificationAdaptive signal subspace projectionASSPEigen-featuresArtificial neural networkANN
原始連結:連回原系統網址new window
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  • 共同引用共同引用:0
  • 點閱點閱:2
期刊論文
1.Harsanyl, J. C.、Chang, C. I.(1994)。Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach。IEEE Transactions on Geoscience and Remote Sensing,32(4),779-785。  new window
2.Ren, H.、Chang, C. I.(2000)。A generalized orthogonal subspace projection approach to unsupervised multispectral image classification。IEEE Trans. Geosci. Remote Sens.,38(6),2515-2528。  new window
3.張麗娜(19970700)。Adaptive Eigendecomposition Algorithms for Eigenstructure-Based Array Signal Processing。中國工程學刊,20(4),365-375。  new window
4.He, H.、Collet, C.(1999)。Combining spectral and textural features for multispectral image classification with artificial neural networks。International Archives of Photogrammetry and Remote Sensing,32(Part7-4-3),W6。  new window
5.Tu, T. M.、Chen, C. H.、Chang, C. I.(1998)。A noise subspace projection approach to target signature detection and extraction in an unknown background for hyperspectral images。IEEE Transactions on Geoscience And Remote Sensing,36(1),171-181。  new window
6.Warner, T. A.、Shank, M.(1997)。An evaluation of the potential for fuzzy classification of multispectral data using artificial neural networks。Photogrammetric Engineering & Remote Sensing,63(11),1285-1294。  new window
會議論文
1.Tian, Y.、Guo, P.、Lyu, M. R.(2005)。Comparative studies on feature extraction methods for multispectral remote sensing image classification。The IEEE International Conference on Systems, Man and Cybernetics。Waikoloa, Hawaii。1275-1279。  new window
2.Chang, L.、Cheng, C. M.(2006)。A combined signal subspace projection and partial filtering approach to target detection for hyperspectral images。IEEE International Geoscience and Remote Sensing Symposium。Colorado。3891-3894。  new window
 
 
 
 
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