Mask-based denoising scheme for ghost imaging

Ghost imaging (GI) is thought of as a promising imaging method in many areas. However, the main drawback of GI is the huge measurement data and low signal-to-noise ratio. In this paper, we propose a novel mask-based denoising scheme to improve the reconstruction quality of GI. We first design a mask through the maximum between-class variance (OTSU) method and construct the measurement matrix with speckle patterns. Then, the correlated noise in GI can be effectively suppressed by employing the mask. From the simulation and experimental results, we can conclude that our method has the ability to improve the imaging quality compared with traditional GI method. (paper)