Images captured in the underwater environment often suffer from color distortion and blurring owing to the effects of light absorption and scattering. An integrative framework is proposed to effectively restore the underwater images. First, a modified color constancy-based algorithm is designed for correcting the color of the underwater images. Second, an effective underwater image degradation model is constructed to model the statistics of the scattering event. Then, the underwater image deblurring is achieved using a group-based sparse representation method. To evaluate the performance of the proposed method, we compare our results with several existing approaches using the subjective technique as well as the objective technique. The results show that the proposed method can achieve better restoration for color fidelity and visibility compared to all other state-of-the-art algorithms.