针对现有光场采集方式中存在的：相机阵列采集方式的硬件成本高，体积庞大；单相机分时采集光场局限采集静态光场；积分成像光场采集得到的光场空间分辨率低等问题。研究了一种基于掩膜(mask)的光场采集与重建方法。建立了光场采集模型，分析了光场在傅里叶域的成像过程；采用了随机衰减掩膜mask对光场信号进行随机编码，得到了被编码的传感器图像；离线学习了过完备光场字典，结合压缩感知理论对编码的传感器图像进行了非线性优化，重新恢复了原始的光场。

In view of the existed problems of the existing light field acquisition methods: high hardware cost and big volume in camera array acquisition; to be limited to static light field in single camera ordinal sampling; low spatial resolution of the light field in integral imaging light field acquisition. A method of light field acquisition and reconstruction based on a mask has been studied. A light field acquisition model is set up. Light field imaging process is analyzed in Fourier domain. Utilizing a random mask to randomly encode the light field, which leads to get a coded sensor image. An overcomplete light-field dictionary is learned offline. The coded sensor image is optimized through compressed sensing and the overcomplete light-field dictionary. The original light field is restored.