TY - JOUR
T1 - How to Evaluate and Remove the Weakened Bands in Hyperspectral Image Classification
AU - Zhang, Huan
AU - Han, Xiaolin
AU - Deng, Jingwei
AU - Sun, Weidong
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - Hyperspectral image classification is mainly based on the spectral information of land covers, but water vapor or Rayleigh scattering will weaken the surface reflectance under the effect of adjacent pixels and thus lead to the reduction of the discriminative information for the subsequent classification tasks. Atmospheric correction for the weakened bands is one of the most traditional ways to deal with this issue, but as a complete atmospheric correction for both of them is difficult, maybe a systematic exclusion of the severely affected bands based on quantitative evaluation is a better choice. In this article, an evaluation-based weaken band exclusion method for the hyperspectral image classification is proposed, trying to remove the severely affected bands without further atmospheric correction. Specifically, an evaluation model to describe how the water vapor and Rayleigh scattering affect the surface reflectance is constructed, by using the statistical relationship between the radiative transfer model and the band weaken index of spectra among the adjacent pixels. Then, with a simulation experiment, it is shown that water vapor and Rayleigh scattering can really weaken the discriminative information of some specific bands, and the band weaken index can serve as an appropriate index to evaluate the weakening degree of those bands. Finally, on this basis, the total framework of evaluation-based weaken band exclusion method is given. The effectiveness and the universality of our proposed method have been verified and compared on four representative tasks of the hyperspectral image classification.
AB - Hyperspectral image classification is mainly based on the spectral information of land covers, but water vapor or Rayleigh scattering will weaken the surface reflectance under the effect of adjacent pixels and thus lead to the reduction of the discriminative information for the subsequent classification tasks. Atmospheric correction for the weakened bands is one of the most traditional ways to deal with this issue, but as a complete atmospheric correction for both of them is difficult, maybe a systematic exclusion of the severely affected bands based on quantitative evaluation is a better choice. In this article, an evaluation-based weaken band exclusion method for the hyperspectral image classification is proposed, trying to remove the severely affected bands without further atmospheric correction. Specifically, an evaluation model to describe how the water vapor and Rayleigh scattering affect the surface reflectance is constructed, by using the statistical relationship between the radiative transfer model and the band weaken index of spectra among the adjacent pixels. Then, with a simulation experiment, it is shown that water vapor and Rayleigh scattering can really weaken the discriminative information of some specific bands, and the band weaken index can serve as an appropriate index to evaluate the weakening degree of those bands. Finally, on this basis, the total framework of evaluation-based weaken band exclusion method is given. The effectiveness and the universality of our proposed method have been verified and compared on four representative tasks of the hyperspectral image classification.
KW - Band weaken index
KW - evaluation model
KW - hyperspectral image (HSI)
KW - land cover classification
KW - weaken band exclusion
UR - http://www.scopus.com/inward/record.url?scp=85214561090&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2025.3526917
DO - 10.1109/TGRS.2025.3526917
M3 - Article
AN - SCOPUS:85214561090
SN - 0196-2892
VL - 63
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 5502515
ER -