A multiframe phase-diversity algorithm for imaging through the turbulent atmosphere tailored to the statistics of coherent light is developed and presented. The problem is posed as a maximum likelihood estimation where pupil-plane intensity data and atmospheric statistics are used to regularize the inverse problem. Reconstruction results characterized by residual mean square error are presented for varying detection parameters. The resulting algorithm appears to be robust under detection noise processes and results in significant improvement of processed images.