Aerial image defogging based on dual-threshold position and transmittance constraint

In order to improve the visibility of aerial image in the foggy weather, an image defogging algorithm based on dual-threshold position and transmittance constraint is proposed. Firstly, according to the features of non-sky and rich details from aerial images, both the gradient threshold and brightness threshold are used to keep positional limitation of the atmospheric light and therefore the accuracy has been improved effectively. Secondly, the transmittance is estimated by creating constraint, then the precise value is obtained by performing bi-exponential edge preserving filtering. Finally, a tone mapping method for restored image is proposed based on the perception law of human vision to the signal fluctuation. Simulation results show that the restored images not only remove fog effectively, but also keep color natural and real. The average entropy and gradient from test images are 7.659 and 16.631, which achieve a degree of improvement compared with other algorithms. The proposed algorithm gets satisfactory restoration for different landforms and detail features, thereby it can meet the application requirement of aerial image defogging.