TY - GEN
T1 - A novel spectrum elaboration method for moving targets based on empirical mode decomposition
AU - Zhang, Miao
AU - Yuan, Ruilin
AU - Shen, Yi
N1 - Publisher Copyright:
© 2018 IEEE
PY - 2018/10/31
Y1 - 2018/10/31
N2 - In order to overcome the noise impact of hyperspectral images during the acquisition process due to target movement and environmental interference, this paper proposes a spectrum elaboration method based on empirical mode decomposition (EMD) for visible and near-infrared hyperspectral image data. The difference with the prior arts is that this method obtains a spectral curve by processing a series of hyperspectral data cubes. The experiments show that this method can obtain the vector of spectral signature that reflects the essential features for the moving object, as the results of spectral angle indicate that discrepancies between non-congeners are greater and similar congeners are more similar, which compared to the gaussian filtering method and the direct averaging method. has a higher accuracy than the traditional method without feature enhancement and has good innovative and practical value.
AB - In order to overcome the noise impact of hyperspectral images during the acquisition process due to target movement and environmental interference, this paper proposes a spectrum elaboration method based on empirical mode decomposition (EMD) for visible and near-infrared hyperspectral image data. The difference with the prior arts is that this method obtains a spectral curve by processing a series of hyperspectral data cubes. The experiments show that this method can obtain the vector of spectral signature that reflects the essential features for the moving object, as the results of spectral angle indicate that discrepancies between non-congeners are greater and similar congeners are more similar, which compared to the gaussian filtering method and the direct averaging method. has a higher accuracy than the traditional method without feature enhancement and has good innovative and practical value.
KW - Empirical mode decomposition
KW - Hyperspectral images
KW - Intrinsic mode function
KW - Spectral signature
UR - https://www.scopus.com/pages/publications/85064153317
U2 - 10.1109/IGARSS.2018.8518800
DO - 10.1109/IGARSS.2018.8518800
M3 - 会议稿件
AN - SCOPUS:85064153317
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 7259
EP - 7262
BT - 2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018
Y2 - 22 July 2018 through 27 July 2018
ER -