Fog removal and enhancement method for UAV aerial images based on dark channel prior

Abstract

The existing UAV aerial image de-fog methods have low image contrast after de-fog, the difference between light and dark image is not obvious, leading to poor de-fog effect. Therefore, an aerial image de-fog enhancement method based on dark channel a priori is proposed. The image variance and absolute gradient mean are combined to get the weight coefficients, and the edge pixels are smoothed by using the multiple decomposition form. The image intensity is calculated and the noise is reduced. A convolution neural network is introduced to calculate the atmospheric transmittance in haze. Based on this, dark channel prior algorithm is used to enhance the light and shade difference of aerial photography image and realise the de-fog enhancement of aerial photography image. To verify the performance of the proposed method, simulation experiments are designed which were compared with the existing methods results in better fog-removing effect, higher contrast and shorter time.