An image defogging algorithm based on attention mechanism and Markov discriminator (PatchGAN) is proposed herein to differentiate features according to the different regional features of foggy images, which cannot be achieved using existing defogging algorithms. Combined with attention mechanism, the proposed algorithm can adaptively assign weights to the features of different regions while using the module with Inception mechanism to predict the globally relevant atmospheric light value more accurately and effectively. The predicted atmospheric light value, transmittance, and foggy image are input into the atmospheric scattering model to obtain the defogged image. Finally, the defogging image is input into PatchGAN to determine whether it is true or false. The experimental results show that the proposed algorithm achieves good defogging effect on indoor and outdoor foggy images and improves the brightness and saturation of defogging images.