In order to solve the problem of large sky or white area failure in a dark channel prior algorithm, a Gaussian decay and adaptive compensation dehazing algorithm combined with scene depth estimation was proposed. Firstly, estimating the scene depth by an approximately positive correlation between the arithmetic mean of the RGB channel scattering intensities and the haze concentration. Then, combined with the edge information of the scene depth, a Gaussian filter is constructed using the difference between adjacent pixels to filter the minimum channel to obtain a Gaussian dark channel. Secondly, using the relationship between the Gaussian dark channel and its Gaussian function, through the relationship between the adjustment factor and the haze concentration, a strategy that combines convolution with scene depth and Gaussian surround function was proposed to obtain the adjustment factor; then, the transmission was adaptively compensated and estimated. Finally, the haze-free image was restored with the atmospheric scattering model. The experimental results show that the proposed algorithm can accurately estimate the transmission based on the operation efficiency. In the objective evaluation, the average number of edges increased by 0.02 while the number of saturated pixels decreased by 0.002. The proposed algorithm can also recover natural and clear haze-free images, especially in the scene depth and the sky area.