General temporal ghost imaging model with detection resolution and noise

Abstract

Improving imaging quality while reducing the sampling time simultaneously is a crucial challenge that limits the practical application of temporal ghost imaging (TGI). To improve the performance of TGI, various methods have been proposed and verified. However, a work analyzing in detail the influence of intensity accuracy and detection noise of TGI is still absent. Here, we establish an evaluation model to quantify the imaging quality of TGI and differential TGI (DTGI). Our model considers the intensity detection accuracy, threshold, and noise of the test path during image reconstruction and quantifies their influences by developing general imaging formulas of (D)TGI. We also simulate the imaging of (D)TGI numerically. The evaluation demonstrates that (D)TGI is relatively not sensitive to detection accuracy and thresholds of the test path, and image quality is degraded slightly even when those parameters turn much worse. (D)TGI is relatively robust to detection noise but will be unable to reconstruct the object when noise is too strong. DTGI does not show clear advantages over TGI. Our work develops an effective model to quantify the image quality with practical parameters and is significant to real applications of (D)TGI.