Haze reduction from remotely sensed data

Abstract

Haze consists of atmospheric aerosols and molecules that scatter and absorb solar radiation, thus affecting the downward and upward solar radiance to be recorded by remote sensing sensors. Haze modifies the spectral signature of land classes and reduces classification accuracy, so causing problems to users of remote sensing data. Hence, there is a need to reduce the haze effects to improve the usefulness of the data. A way to do this is by integrating spectral and statistical approaches. The result shows that the haze reduction method is able to increase the accuracy of the data statistically and visually.