For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will be different salient features when use different normalization method. In this letter, we report the effect on classifiers by different normalization methods and recommend the best normalization methods for classifier after analyzing the impact of different normalization methods on classifiers. Pavia University datasets, Indian Pines datasets and Kennedy Space Center datasets will apply to several typical classifiers in order to evaluate and analysis the impact of different normalization methods on typical classifiers.
Cite
@article{arxiv.1710.02939,
title = {Does Normalization Methods Play a Role for Hyperspectral Image Classification?},
author = {Faxian Cao and Zhijing Yang and Jinchang Ren and Mengying Jiang and Wing-Kuen Ling},
journal= {arXiv preprint arXiv:1710.02939},
year = {2017}
}