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UAV aerial image defogging based on optimum of quality evaluation

Unmanned aerial vehicles have been widely used in military and civil areas, which requires vision processing in explicit usage scenario. Existence of haze or fog can influence the context awareness capability of the aerial vehicles and makes affectation on target tasks. The captured images in hazy scenes suffer from degradation problems including poor contrast, color distortion, incomplete information, which lead to many difficulties in the follow-up processing. A simple and effective single image dehazing algorithm based on atmospheric scattering model and the optimum of image quality evaluation is proposed in this paper. Three image quality evaluation parameters: image entropy, standard deviation, and Fourier amplitude are combined to establish and the image quality evaluation function. On the basis of quality evaluation function, the image with the optimum of quality evaluation among the potential defogging images is chosen as the best result. Results show that this method has lower computational complexity, simplified operations and improved real-time performance.