Single image dehazing is very important in intelligent vision systems. Since the dark channel prior (DCP) is invalid in bright areas such as the sky part of the image and will cause the recovered image to suffer severe distortion in the bright area. Therefore, we propose a novel dehazing method based on transmission map segmentation and prior knowledge. First, we divide the hazy input into bright areas and non-bright areas, then estimate the transmission map via DCP in the non-bright area, and propose a transmission map compensation function for correction in the bright area. Then we fuse the DCP and the bright channel prior (BCP) to accurately estimate the atmospheric light, and finally restore the clear image according to the physical model. Experiments show that our method well solves the DCP distortion problem in bright regions of images and is competitive with state-of-the-art methods.