CADCP: a method for chromatic haze compensation on remotely sensed images

Abstract

Remote sensing images often suffer from different types of haze. Its presence significantly complicates remotely sensed image analysis that is crucial for monitoring of land state and precision agriculture. Currently existing remote sensing dehazing methods are designed for achromatic haze, but in cases such as smoke from fires or sandstorms, the haze may have its own pronounced coloration. In this paper we propose a new hazed image formation model that considers chromatic haze. Using this model we propose a new single image dehazing method CADCP that is based on color attenuation and dark channel priors. For quality assessment of the proposed method we generated a dataset of remotely sensed images with simulated chromatic haze. The generated dataset includes data with various haze spatial distribution and density. Quality evaluation results including qualitative and quantitative approaches demonstrated better results of the proposed method comparing with other existing methods.