Adaptive Single Image Dehazing Using Joint Local-Global Illumination Adjustment

Haze has a serious impact on the outdoor optical imaging systems, and it will result in image blurring, color shift, and saturation reduction. Recently, many single image dehazing algorithms have been proposed for practical applications, such as surveillance. However, since the widely-used global atmospheric light in image dehazing fails to well describe the local illumination differences of images, these algorithms fail to well adapt to scenes with different haze concentrations and lighting conditions. Therefore, this paper proposes an adaptive single image dehazing algorithm using joint local-global illumination adjustment. A local illumination estimation for hazy image is proposed to replace the global atmospheric light constant in the atmospheric scattering model, and it can better adapt to the local differences of image illumination. Correspondingly, the global atmospheric light constant is proposed to be utilized to adaptively compensate the illumination intensity, which may better overcome the dark illumination problem within the dehazed image. The experimental results demonstrate that the proposed algorithm can outperform the state-of-the-art algorithms in terms of not only the dehazing effect but also the adaptability.