To address the problems of detail loss, low brightness and color distortion when processing sea fog images by dark channel prior defogging algorithm, this paper proposes a sea fog image defogging algorithm based on sky region segmentation. First, accurate segmentation of the sky region is achieved through threshold segmentation and region growing. On this basis, an approach with stronger anti-interference capabilities is used to optimize the atmospheric light intensity, the median value of the top 0.1% pixels belonging to the region with the highest luminance is chosen as the atmospheric light intensity. Second, the transmittance is refined using fast bootstrap filtering and an adaptive correction factor is introduced to adjust and optimize the transmittance mapping. Finally, the obtained transmittance and atmospheric light intensity are utilized with an atmospheric scattering model to restore the defogging image. Experimental results demonstrate that the algorithm significantly enhances evaluation metrics such as structural similarity and peak signal-to-noise ratio, effectively improving the quality of the defogging image.