Dehazing of Aerial Images by Dark Channel and Gamma Correction

Hazed blankets during poor weather conditions make it very tough to interpolate the details from images captured by the satellite. The low temperatures in winter exacerbate smog by causing temperature inversions. By this paper, we present an effective method to improve the contrast of hazed images by computing its dark channel image, calculating the atmospheric light, recovering the scene radiance and refining it by gamma correction. On testing the algorithm on real aerial images, we obtain significant results. This method is applicable to colored and gray-scale images. The experimental results show the SSIM index values and correlation factor nearly equal to one, after executing the algorithm on hazed images.