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压缩成像是压缩传感理论的重要应用领域之一,可以用比Nyquist测量数目少的测量值捕获充分信息重建稀疏或可压缩图像。在研究现有的压缩成像方法的基础上,给出一种新的循环-托普利兹块相位掩模矩阵可压缩双透镜成像方法。模拟实验结果表明新的相位掩模矩阵成像方法可以在欠采样的情况下有效地获得图像信息来重建原始图像。新方法的研究为确定性测量在压缩成像领域的应用提供了更多的支撑,在拥有托普利兹和循环确定性测量优点的同时,还拥有自身的块结构特点,可以进一步减少物理实现成本。
Compressive imaging is one of the most important applications of compressive sensing theory. It can capture sufficient information to reconstruct sparse or compressible images with less than the Nyquist measurements. Based on the research of the existing compressive imaging methods, a new compressible two-lens imaging method based on a cyclic-Toprec block phase mask matrix is proposed. Simulation results show that the new phase mask matrix imaging method can effectively obtain the image information to reconstruct the original image in the case of undersampling. The new methodologies provide more support for the use of deterministic measurements in the field of compression imaging, and have the advantage of own block structure while taking advantage of Toledoze and cyclically deterministic measurements, further reducing physical implementation costs.