When can the minimum volume enclosing simplex identify the endmembers correctly when there is no pure pixel?

Wing Kin Ma, Chia Hsiang Lin, Wei Chiang Li, Chong Yung Chi

研究成果: Conference contribution

摘要

In blind hyperspectral unmixing, it has been commonly believed that the minimum volume enclosing simplex (MVES) criterion is robust against lack of pure pixels. Specifically, such a belief has been based on empirical experience, where extensive numerical results showed that MVES-based algorithms may identify the underlying endmembers quite accurately under high signal-to-noise ratios and without pure pixels. In this paper, we report some theoretical results on the endmember identifiability of the MVES criterion in the noiseless case. We employ an assumption that is a two-mixture generalization of the pure-pixel assumption; particularly, we require a set of pixels, each being constituted by only two endmembers (rather than one as in the pure-pixel assumption), to exist in the data set. Under this assumption and some rather mild condition, we show that the MVES solution perfectly identifies the true endmembers. Numerical simulation results are provided to verify our theoretical results.

原文English
主出版物標題2015 7th Workshop on Hyperspectral Image and Signal Processing
主出版物子標題Evolution in Remote Sensing, WHISPERS 2015
發行者IEEE Computer Society
ISBN(電子)9781467390156
DOIs
出版狀態Published - 2015 七月 2
事件7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2015 - Tokyo, Japan
持續時間: 2015 六月 22015 六月 5

出版系列

名字Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
2015-June
ISSN(列印)2158-6276

Conference

Conference7th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2015
國家/地區Japan
城市Tokyo
期間15-06-0215-06-05

All Science Journal Classification (ASJC) codes

  • 電腦視覺和模式識別
  • 訊號處理

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