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Computational ghost imaging system with 4-connected-region-optimized Hadamard pattern sequence
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AI
DOI：10.1016/j.optlaseng.2020.106105.png)
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Abstract
En 中文
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.
Keywords:
Computational imaging
Hadamard pattern
Connected region
Ghost imaging
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