Due to the intrinsic limitations of hyperparameters, most dehazing algorithms easily suffer from overenhancement or staircase artifacts. To suppress these problems, a spatially adaptive total generalized variational (TGV)-based single image dehazing algorithm is developed. The algorithm contain two modules, i.e., an adaptive coarse transmission map estimation module and a spatially adaptive TGV-based transmission refine module. The adaptive coarse transmission map estimation module is designed to prevent the dehazing result from being overenhanced with a dark channel-based adaptive control parameter. The TGV-based transmission refine module is designed to refine the coarse transmission with a texture prior-based spatially adaptive TGV-regularized variational model. Numerous experiments reveal that the proposed algorithm is comparable with or even outperforms the state-of-the-art techniques.