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題 名 | 高光譜資料之光譜差異分析及量化指標=The Analysis and Quantification of Spectral Differences for Hyperspectral Data |
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作 者 | 王儷蓉; | 書刊名 | 航測及遙測學刊 |
卷 期 | 4:1 1999.03[民88.03] |
頁 次 | 頁19-33 |
分類號 | 440.98 |
關鍵詞 | 高光譜資料; 光譜分析; 光譜差異; Hyperspectral data; Spectral analysis; Spectral difference; |
語 文 | 中文(Chinese) |
中文摘要 | 近年來由於高光譜影像掃描器的發展,使得高光譜影像所包含之光譜資訊較多光 譜影像來得豐富且精細。理論上,應用含有豐富又精細光譜資訊的高光譜資料,應有助於分 辨更細微差異之地物。然而以傳統之統計分類技術應用於高光譜影像時,不僅無法提昇分類 之層次與精度,且會產生分類效率慢以及需要大量訓練資料等問題。為了找出問題所在,首 先由資料表現觀點論述高光譜資料在不同空間之表示方式及其特性;再從不同表示空間中分 析光譜之差異性;最後將光譜差異引伸至類別差異性,利用傳統多光譜類別分離度理論探討 高光譜類別分群之方法及其效力。 |
英文摘要 | Recently due to the advance of image scanning technology, hyperspectral image scanners which have tens or even hundreds spectral bands have been developed. Comparing to the traditional multispectral images, hyperspectral images have richer and finer spectral information than the images we can obtain before. Theoretically, using hyperspectral images should increase our abilities in classifying land use/cover types. However, when traditional classification technologies are applied to the analyzing processes of hyperspectral images, people are usually disappointed by the consequences of low efficiency, needing a large amount of training data, and barely improvement of classification accuracy. In order to solve this problem, technologies of hypersepctral data analyses and processes must be developed. First, this paper illustrates the characteristics of three different spaces (Image, Spectral and Feature) in which hyperspectral data can be inspected. Then, some fundamental statistical theories and graphical presentations of the statistics for hyperspectral images are introduced. Then, spectral differences are analyzed in difference spaces. In addition to spectral differences, differences between two hyperspectral data classes are also analyzed. |
本系統中英文摘要資訊取自各篇刊載內容。