A multi-channel image blind restoration algorithm based on single total variation regularity can cause a ringing effect and loss high-frequency information in restored images. To solve this problem, a multi-channel image blind restoration algorithm based on total variation and dark pixels is proposed using the non-sparseness of dark pixels in blurred images. Solving the problem of total variation and dark pixel double regularization model is difficult. To address the difficult problem, the split Bregman optimization algorithm is used to ensure convergence of the results, the global problem is decomposed into independent sub-problems, and the image and point spread function are solved alternately to restore the target images. The experimental results demonstrate that the proposed algorithm can effectively remove image blurring, suppress ringing effects, and restore high-quality clear images. Compared to an algorithm with the total variation regular term, the peak signal-to-noise ratio of the proposed algorithm improves by 0.12 dB--5.86 dB, and the structural similarity improves by 0.014--0.125.