Computational ghost imaging system with 4-connected-region-optimized Hadamard pattern sequence

Heng Wu, Genping Zhao, Ruizhou Wang, Huapan Xiao, Daodang Wang, Jian Liang, Lianglun Cheng, Rongguang Liang

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


We propose a computational ghost imaging system based on the Hadamard patterns. A 4-connected-region-based method is proposed to optimize the Hadamard pattern sequence and a differential decomposition method is developed to construct a sequence that can be shown on the light modulation devices with the optimized pattern sequence. Finally, the image is reconstructed by the second-order correlation algorithm. Both numerical model and experimental setup are established and a series of experiments are implemented. The imaging performance of the proposed method is validated by comparing with the results from the default order of the Hadamard pattern sequence, Russian-dolls ordering and fast Walsh-Hadamard transform. The proposed system can realize high quality imaging with a low sampling ratio (5%–10%), and it requires much less measurement numbers for imaging.

Original languageEnglish (US)
Article number106105
JournalOptics and Lasers in Engineering
StatePublished - Sep 2020


  • Computational imaging
  • Connected region
  • Ghost imaging
  • Hadamard pattern

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Mechanical Engineering
  • Electrical and Electronic Engineering


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