We present a novel collaborative and compressive high-resolution image acquisition method in this paper. The proposed approach acquires several coded low resolution observations via the designed image formation process. The imaging process is achieved via random convolution followed with subsampling, which is practical for hardware implementation. The latent high resolution image is recovered via a joint optimization scheme in a collaborative manner. An efficient optimization algorithm is developed for recovering the latent high-resolution image. Experimental results compared with several related imaging schemes have clearly demonstrated the effectiveness of the propose method.