We explore the relationship between compressive-sensing measurements and differential image motion. Our work shows that, given modest constraints on the measurements and image motions, we can omit the computationally expensive compressive-sensing reconstruction step and obtain more accurate motion estimates with significantly less computation time. We also formulate compressive-sensing reconstruction problems that incorporate known image motion, demonstrating improved performance in compressive-sensing video reconstruction compared to state-of-the-art methods.