Title: VERIFICATION OF STATISTICAL PROPERTIES FOR HYPERSPECTRAL IMAGES: HETEROSCEDASTICITY AND NON-STATIONARITY

Year of Publication: 2013
Page Numbers: 191-195
Authors: Jihao Yin, Chao Gao, Jianying Sun
Conference Name: The Third International Conference on Digital Information Processing and Communications (ICDIPC2013)
- United Arab Emirates

Abstract:


This paper investigates the heteroscedasticity and non-stationarity, two statistical properties, of hyperspectral remote sensing data. In the field of mathematical sciences, a collection of variables is heteroscedastic if there are sub-populations that have different variances or volatilities than others, while a non-stationary process refers to a stochastic process whose joint probability distribution are changing when shifted in time or space. To be treat as sequences, hyperspectral data are investigated via Bartlett Test and Wald-Wolfowitz Runs Test to verify the heteroscedasticity and non-stationarity, respectively. Most experimental results fail to pass Bartlett Test and Wald-Wolfowitz Runs Rest statistically significant, indicating that both heteroscedasticity and non-stationarity are intrinsic properties of spectral response sequence.