压缩感知重建数字同轴全息

Reconstruction of Digital Inline Hologram with Compressed Sensing

数字重建是数字全息技术的关键步骤。传统的重建算法存在共轭像、聚焦物体与背景离焦物体相互干扰等问题。应用新兴的压缩感知技术,研究了全息图像的稀疏重建。基于衍射的线性运算,导出了利用压缩感知重建数字同轴全息三维空间的算法。利用该算法对颗粒的模拟全息图和数字显微全息实验全息图进行了重建,并将重建结果与传统的卷积重建结果进行了对比。结果表明,压缩感知技术能有效提高数字全息重建截面图像质量,利用25%全息图数据也能实现较好的重建,且具有较好的聚焦和抗噪声干扰能力。

Numerical reconstruction is a key procedure of digital holography. Classical reconstruciton algorithms are characterized by the twin images, superimposition of in-focus and out-of-focus object, and so on. Application of the new compressive sensing theory to sparsity reconstruction of digital inline holography is investigated. Based on the linear operator of diffraction model, the algorithm for the reconstruction of digital inline holography using compressive sensing is derived. Holograms of particle field from both simulation and micro digital inline holography are reconstructed, and the reconstructed particle field with compressive sensing algorithm is compared with that of convolution algorithm. Results show that the compressive sensing algorithm can improve the quality of reconstructed planes, and can reconstruct the particle field with good accurary with even 25% of the hologram. It also shows potential in focusing performance and robustness to noise.