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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38664
Title: | 應用NMF方法分析多頻譜遙測影像 Unsupervised Classification of Remote Sensing Imagery With Non-negative Matrix Factorization |
Authors: | "Kuang-De, Ou Yang" 歐陽廣德 |
Advisor: | 劉長遠(Cheng-yuan Liou) |
Keyword: | 非監督式分類,遙測影像,非負矩陣分解, Unsupervised Classification,Remote Sensing,Non-negative Matrix Factorization,Fuzzy C Means,Partitioned Noise Adjusted Principle Component Analysis, |
Publication Year : | 2005 |
Degree: | 碩士 |
Abstract: | An unsupervised classification method provides the interpretation, feature extraction and
endmember estimation for the remote sensing image data without any prior knowledge about the ground quality. We explore such method and construct an algorithm based on the non-negative matrix factorization (NMF). The use of the NMF is to match the non-negative property in sensing spectrum data.. The data dimensionality is estimated by using the partitioned noise-adjusted principlal component analysis (PNAPCA). The initial matrix used to start the NMF is obtained by using the fuzzy c-mean (FCM). This algorithm is capable to produce a region- or part-based representation of objects in images. Both simulated and real sensing data are used to test the algorithm. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/38664 |
Fulltext Rights: | 有償授權 |
Appears in Collections: | 資訊工程學系 |
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File | Size | Format | |
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ntu-94-1.pdf Restricted Access | 802.55 kB | Adobe PDF |
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