Remote Sensing and Natural Image Dehazing using DCP based IDERS Framework

Abstract

Generally remote sensing images are in hazy conditions such as fog, snow, thin cloud, dust etc., which results in contrast degradations in image. This work is based on the Dark Channel prior (DCP) to eliminate the haze effect on remote sensing images. In this model both natural images and remote sensing images Dehazingis possible. In the enhancement of satellite image properties several steps are involved, the first step is to identify whether the image is natural image or remote sensing image and restore it for the purpose of removing haze. By using air light values further, the iteration takes place with the help of DCP to remove dust and then the haze is eliminated by applying Iterative dehazing method for remote sensing image (IDERS) model. The output image obtained after Low light image enhancement (LIME) process is free from haze, brightness is enhanced. The simulation results shows that the performance of proposed method is improved as compared to the state of art approaches.