Improved dark channel prior dehazing approach using adaptive factor

Image has important applications in many fields such as marine surveillance, environment monitoring and so on. The scattering effects of the atmospheric particles in the air play a main role of resulting in contrast reduction and color fading. For dealing with this challenging but imperative issue, there are numerous researchers have strove for this scientific field and published a plenty of findings about restoring the foggy image. In generally, the foggy image always includes the sky and non-sky regions while the pixel values in this two distinguished regions is extremely different. The dark channel prior algorithm has been considered as one effective dehazing approach which only employs one constant factor for the overall image regardless of the scene pattern. This imprudent procedures always leads to more darkness image color and fails to achieve excellent results. For dealing with this challenging but imperative issue, we propose one improved dark channel prior dehazing approach using adaptive factor. In our algorithm, the foggy image is segmented into sky region and non-sky region respectively, the critical parameters i.e. light intensity and transmission ratio are obtained based on different factors. Some comparative experiments have also been conducted for validating dehazing performance of the proposed approach.