Spectral derivative feature coding for hyperspectral signature analysis

中國醫藥大學機構典藏 China Medical University Repository, Taiwan > 台中附設醫院 > 期刊論文 > Item 310903500/5452

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题名:	Spectral derivative feature coding for hyperspectral signature analysis
作者:	張建禕(Chein-I Chang);(SumitChakravarty);陳享民(Hsian-Min Chen);歐陽彥杰(Yen-ChiehOuyang)
贡献者:	中國附醫醫學研究部共同實驗室
日期:	2009-03
上传时间:	2009-08-24 14:42:55 (UTC+8)
摘要:	This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC.
關聯:	PATTERN RECOGNITION 42(3)395~408
显示于类别:	[台中附設醫院] 期刊論文

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