Aiming at the varying scene light in imaging process and difference between the haze relevant features in image dehazing，a channel attention network and fuzzy partition entropy with graph cut for single image dehazing based on the improved atmospheric scattering model with varying scene light is proposed. Firstly， the encoder-decoder network with channel attention mechanism is utilized to estimate transmission map. Then the proposed channel attention module is applied in the end of encoder and the beginning of the decoder for assigning different weights to different haze relevant feature maps and obtaining accurate transmission map. Then， the fuzzy partition entropy combined with graph cut is used to segment the transmission map into distant scene， middle scene and close scene covered with varying scene light. This scheme combines spatial correlation and fuzzy partition entropy， solving misclassified problem introduced by the threshold-based segmentation. Finally， a clear image is obtained with the predicted transmission map， estimated scene light and atmospheric light. Extensive experiments demonstrate that this method achieves promising effective on synthetic images and real images. Comparing with exiting methods， our method improves dehazing results in both peak signal to noise ratio and structural similarity. The average running time for handling single hazy image is 3.9 s.