Structured illumination microscopy (SIM) has been widely applied to investigating fine structures of biological samples by breaking the optical diffraction limitation. So far, video-rate imaging has been obtained in SIM, but the imaging speed was still limited due to the reconstruction of a super-solution image through multi-sampling, which hindered the applications in high-speed biomedical imaging. To overcome this limitation, here we develop compressive imaging-based structured illumination microscopy (CISIM) by synergizing SIM and compressive sensing (CS). Compared with conventional SIM, CISIM can greatly improve the super-resolution imaging speed by extracting multiple super-resolution images from one compressed image. Based on CISIM, we successfully reconstruct the super-resolution images in biological dynamics, and analyze the effect factors of image reconstruction quality, which verify the feasibility of CISIM. CISIM paves a way for high-speed super-resolution imaging, which may bring technological breakthroughs and significant applications in biomedical imaging.