Parallel magnetic resonance imaging (pMRI) cannot achieve its maximum reduction factor due to practical limitations. The combination of pMRI and distributed compressed sensing (DCS) for further acceleration is of great interest. In this paper, we propose a method to combine sensitivity encoding (SENSE), one of the standard methods for pMRI, and M-FOCUSS, an algorithm solving DCS reconstruction problem. The proposed method first employs M-FOCUSS algorithm to simultaneously reconstruct a set of aliased reduced field-of-view (FOV) images for each channel, and then applies cartesian SENSE to reconstruct the final image. The experimental results demonstrate that the proposed method outperforms the existing methods with the same reduction factor.