Haze removal concept in remote sensing

Atmospheric haze causes visibility to drop, therefore affecting data acquired using optical sensors on board remote sensing satellites. Haze modifies the spectral signatures of land cover classes and reduces classification accuracy so causing problems to users of remote sensing data. This paper addresses general concepts of haze removal from remote sensing data. Degradation of satellite data is caused by two key components, i.e. haze scattering and signal attenuation. In developing the concept, a statistical model that makes use both components is used. The former is represented by a weighted haze mean while the latter is represented by a haze randomness component that deals with the signal attenuation. The results show that haze scattering can be removed by subtracting an estimated weighted haze mean while signal attenuation can be removed by applying a spatial filter.