When the spatial frequencies of the object are insufficiently sampled, the reconstruction of ghost imaging will suffer from repetitive visual artifacts, which cannot be effectively tackled by existing ghost imaging reconstruction techniques. In this Letter, extensions of the CLEAN algorithm applied in ghost imaging are explored to eliminate those artifacts. Combined with the point spread function estimation using the second-order coherence measurement in ghost imaging, our modified CLEAN algorithm is demonstrated to have a fast and noteworthy improvement against the spatial-frequency insufficiency, even for the extreme sparse sampling cases. A brief explanation of the algorithm and performance analysis are given.

中文翻译：

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空间频率稀疏的重影成像的图像恢复

当对象的空间频率采样不足时，重影成像的重建将遭受重复的视觉伪像的困扰，而现有的重影成像重建技术无法有效地解决这些问题。在这封信中，探讨了应用于幻影成像的CLEAN算法的扩展，以消除这些伪影。结合在幻影成像中使用二阶相干测量的点扩展函数估计，我们的改进的CLEAN算法被证明具有针对空间频率不足的快速而显着的改进，即使在极端稀疏的采样情况下也是如此。给出了该算法的简要说明和性能分析。