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Simple Denoising Method for Novel Speckle-shifting Ghost Imaging with Connected-region Labeling

Yuan, Sheng;Liu, Xuemei;Bing, Pibin

  • Received : 2018.08.15
  • Accepted : 2019.04.16
  • Published : 2019.06.25

Abstract

A novel speckle-shifting ghost imaging (SSGI) technique is proposed in this paper. This method can effectively extract the edge of an unknown object without achieving its clear ghost image beforehand. However, owing to the imaging mechanism of SSGI, the imaging result generally contains serious noise. To solve the problem, we further propose a simple and effective method to remove noise from the speckle-shifting ghost image with a connected-region labeling (CRL) algorithm. In this method, two ghost images of an object are first generated according to SSGI. A threshold and the CRL are then used to remove noise from the imaging results in turn. This method can retrieve a high-quality image of an object with fewer measurements. Numerical simulations are carried out to verify the feasibility and effectiveness.

Keywords

Ghost imaging;Edge detection;Connected-region labeling

Acknowledgement

Supported by : National Natural Science Foundation of China