Spectroscopy and Spectral Analysis, Volume. 42, Issue 4, 1285(2022)
Adaptability Analysis of Multiple Features Detection Algorithms Based on Fusion Degree Model Between Target and Environment
[2] Wang N, Zhai Y, Zhang L et al[D]. IEEE Geoscience Remote Sensing Letter, 13, 1059(2016).
[7] Ingram J, Lo E. Hyperspectral Anomaly Detection Based on Minimum Generalized Variance Method[D]. Proc SPIE, 6966, 696603(2008).
[9] Chang C I, Hsueh M, Ren H et al[D]. Proc SPIE, 5159, 339(2004).
[12] Chang C I. Hyperspectral Data Processing: Algorithm Design and Analysis[D]. John Wiley & Sons(2013).
[14] Herweg J A, Kerekes J P, Weatherbee O et al[D]. Proc SPIE, 8390, 839028(2012).
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Xian-ming DENG, Tian-cai ZHANG, Zeng-can LIU, Zhong-sheng LI, Jie XIONG, Yi-xiang ZHANG, Peng-hao LIU, Yi CEN, Fa-lin WU. Adaptability Analysis of Multiple Features Detection Algorithms Based on Fusion Degree Model Between Target and Environment[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1285
Category: Research Articles
Received: Dec. 11, 2020
Accepted: --
Published Online: Jul. 25, 2023
The Author Email: Tian-cai ZHANG (cenyi@radi.ac.cn)