Remote sensing image uneven haze removal based on correction of saturation map

Abstract

Remote sensing images are frequently affected by the random haze. An efficient method to remove uneven haze is proposed based on dark channel prior (DCP) corrected by saturation map and atmospheric haze model with consideration of multiple atmospheric scattering effects. First, the non-negligible atmospheric multiple scattering phenomenon is simulated by atmosphere point spread function, and the atmospheric multiple scattering haze model is established. Second, an effect method is proposed to calculate the saturation map to correct the DCP, which is used to eliminate the intensity residual of remote sensing images and re-establish the transmission calculation formula. Finally, the image is entered into the integrated restoration framework to remove the haze. Due to the correction of the saturation map, this method can effectively remove the inhomogeneous haze and retain detailed information in the haze-free areas. Compared with other excellent dehaze approaches, qualitative and quantitative experiments are carried out to demonstrate that the proposed method can effectively recover scenes in hazy regions and can retain more detailed information in haze-free regions.