Sun Da, Luo Zhenpeng, Su Ping, Ma Jianshe, Cao Liangcai
Appl Opt. 2021 Feb 1;60(4):A111-A119. doi: 10.1364/AO.404341.
In this paper, we quantified and analyzed the impact of the norm and total variation (TV) norm sparse constraints on the reconstruction quality under different interlayer spacings, sampling rates, and signal-to-noise ratios. For high-quality holograms, the results of compressive-sensing reconstruction using norm achieved higher quality than those by the TV norm. In contrast, for low-quality holograms, the quality of TV-norm-based reconstruction results was relatively stable and better than that of norm. In addition, we explained why interlayer spacing cannot be smaller and recommend the use of axial resolution of the digital holography system as the interlayer spacing. The conclusions are valuable in the choice of sparse constraints in compressive holographic tomography.
在本文中，我们量化并分析了在不同层间距、采样率和信噪比条件下， 范数和总变差（TV）范数稀疏约束对重建质量的影响。对于高质量全息图，使用 范数进行压缩感知重建的结果比使用TV范数的结果质量更高。相反，对于低质量全息图，基于TV范数的重建结果质量相对稳定且优于 范数的结果。此外，我们解释了层间距为何不能更小，并建议将数字全息系统的轴向分辨率用作层间距。这些结论对于压缩全息层析成像中稀疏约束的选择具有重要价值。
