In an effort to improve image SNR per unit time and effective resolution in 19F-fluorinated gas ventilation imaging the application of compressed sensing was investigated. Simulations of sparse sampling were performed using a 3D 3He ventilation imaging dataset as a gold standard. Sparse and fully sampled image fidelity was quantified by the mean-square error and coefficient of variation of signal intensity. Simulations of low resolution and sparsely sampled images with equivalent acceleration factor were also compared. Based on the simulations prospective lung images using sparse sampling with C3F8 gas were then acquired in a healthy volunteer with acceleration factor of 4.