To solve the problem of blurring and degradation of images captured in foggy conditions and to overcome the limitations of traditional dehazing algorithms based on prior of dark channels,a dehazing algorithm using wavelet transform and using prior theories of dark and bright channels is proposed.By using the prior theories of dark and bright channels,the corresponding atmospheric light value and transmittance are obtained respectively,and the transmittance of dark channels obtained from multi-scale filter windows is fused by using the wavelet transform.The final atmospheric light value and transmittance are obtained by using linear fitting function and guided filter function,and the clear haze-free image is restored by using the atmospheric scattering model.Finally,the subjective and objective analysis methods are used to simulate and compare the proposed algorithm with the previous representative dehazing algorithms.The experimental results show that the proposed algorithm can effectively remove the haze in the original image on the premise of ensuring the real-time performance,and it avoids the color distortion caused by excessive enhancement in the traditional dehazing algorithms.It performs well in terms of subjective visual effects,and is also excellent in terms of objective evaluation indexes,which verify the feasibility,effectiveness and superiority of the proposed algorithm.