Implementation of IDERS Based Deep Fusion Network for Single Image Haze Removal
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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 DE hazingis 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 airlight 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.
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