Introduction: Two fundamental principles behind hyperspectral imaging

研究成果: Chapter

1 引文 斯高帕斯(Scopus)

摘要

This chapter explores two fundamental principles, pigeon-hole principle and orthogonality principle, behind design and development of hyperspectral image processing algorithms in various applications. The pigeon-hole principle has found its applications in estimating the number of endmembers required by spectral unmixing, the number of spectrally distinct signatures by virtual dimensionality (VD), orders of low rank and sparse representation (LRaSR)/low rank and sparse matrix decomposition (LRaSMD), the number of bands to be selected for band selection (BS) and number of bands to be sampled for band sampling (BSam). The orthogonality principle can be used as a criterion to derive the orthogonal subspace projection (OSP) technique in developing algorithms for finding endmembers, detecting subpixel targets, anomalies as well as OSP-based LRaSMD in target/anomaly detection, and OSP-based detection theory applied to classification.

原文English
主出版物標題Advances in Hyperspectral Image Processing Techniques
發行者Wiley-Blackwell
頁面3-40
頁數38
ISBN(列印)9781119687788
DOIs
出版狀態Published - 2022 11月 11

All Science Journal Classification (ASJC) codes

  • 一般工程

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