压缩成像是一种基于压缩传感(CS)理论的新成像方法,其优点是可以用比传统的Nyquist采样定理所需测量数目少得多的测量值重建原稀疏或可压缩图像。在研究Bernoulli和Toeplitz测量矩阵的基础上,提出一种新的随机间距稀疏三元Toeplitz相位掩模矩阵。实验结果表明,在可压缩双透镜成像系统中,与Bernoulli和Bernoulli-Toeplitz相位掩模矩阵相比,新相位掩模矩阵的成像信噪比与之相当。但是随机独立变元个数和非零元个数显著减少,在数据存储与传输时更具优势,物理上更易实现,甚至重建时间是只有它们的21%～66%。 Compression imaging is a new imaging method based on the theory of compressive sensing (CS), which has the advantage that the original sparse or compressible image can be reconstructed with far fewer measurements than the traditional Nyquist sampling theorem. Based on the study of Bernoulli and Toeplitz measurement matrices, a new sparse ternary Toeplitz phase mask matrix is ​​proposed. Experimental results show that the imaging phase noise ratio of the new phase mask matrix is ​​equivalent to that of Bernoulli and Bernoulli-Toeplitz phase mask matrices in compressible two-lens imaging systems. However, the number of stochastic independent variables and non-zero elements is significantly reduced, which is more advantageous in data storage and transmission and is physically easier to achieve. Even the reconstruction time is only 21% -66% of them.