A Fast Image Dehazing Algorithm Using Morphological Reconstruction


It is common to use outdoor photos for surveillance, remote sensing and autonomous navigation, among other things. With these photographs, the biggest problem arises from the effects of environmental pollution: such as dust and water droplets in the air that contribute to haze and smog that degrades the image. Computer vision systems rely on the reduction of this form of deterioration. Transmission maps, also known as depth maps, are the primary focus of current research in dehazing techniques. The quality of the image restoration is directly related to the quality of the transmission maps. A new restoration approach is presented that uses a single image to lessen the pollution impacts and is based on the dark channel prior and the use of morphological reconstruction for fast computing of transmission maps. This paper.. To compare the proposed algorithm's performance to previous dehazing approaches, the peak signal-to-noise ratio and structural similarity index metrics were used. The findings show that the suggested algorithm outperforms other recently introduced approaches.

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