Study of modified band selection methods of hyperspectral image based on optimum index factor

Abstract

As hyperspectral remote sensing image have the features of high spectral resolution, high dimension, it brings a serious problem of choosing the appropriate band combination from numerous bands. To solve the problem，the present paper, basing on Optimum Index Factor, proposes a modified band selection algorithm. It aims to reduce the dimension through the improved block adaptive band selection. According to the strong correlation among the bands of hyperspectral remote sensing image，the paper introduces hyperspectral band selection method based on the correlation between bands. The modified algorithm can overcome some shortages of Optimum Index Factor, such as inefficient of selecting bands. However, it can also remain some characteristics from Optimum Index Factor. For instance, the selected band combination, through the modified algorithm, can retain rich amount of information and weak correlation between the selected bands. And the compute complication is decreased rapidly. Taking Hyperion hyperspectral remote sensing image from EarthObserving-1 as example, the present paper contrast the practical effect of the modified algorithm of sub regional selection band and Optimum Index Factor.