2019
DOI: 10.1364/oe.27.036505
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Image watermarking and fusion based on Fourier single-pixel imaging with weighed light source

Abstract: In previous single-pixel imaging systems, the light source was generally idle with respect to time. Here, we propose a novel image fusion and visible watermarking scheme based on Fourier single-pixel imaging (FSPI) with a multiplexed time-varying (TV) signal, which is generated by the watermark pattern hidden in the light source. We call this scheme as TV-FSPI. With TV-FSPI, we can realize high-quality visible image watermarking, encrypted image watermarking and full-color visible image watermarking. We also d… Show more

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Cited by 23 publications
(2 citation statements)
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“…Ghost imaging (GI) is an imaging technique that generates the image of an object by calculating the second-order correlation function between two light beams [1][2][3][4][5][6]. Ghost imaging has been widely researched in recent years [7][8][9][10][11][12][13][14][15][16]; it has important applications in many fields such as cryptography [17,18], lidar [19,20], medical imaging [21,22], micro object imaging [23,24], three-dimensional imaging [25][26][27][28] and single-pixel imaging [29][30][31][32][33]. In many practical scenes, GI is subject to interference from the transmission medium and from optical background noise.…”
Section: Introductionmentioning
confidence: 99%
“…Ghost imaging (GI) is an imaging technique that generates the image of an object by calculating the second-order correlation function between two light beams [1][2][3][4][5][6]. Ghost imaging has been widely researched in recent years [7][8][9][10][11][12][13][14][15][16]; it has important applications in many fields such as cryptography [17,18], lidar [19,20], medical imaging [21,22], micro object imaging [23,24], three-dimensional imaging [25][26][27][28] and single-pixel imaging [29][30][31][32][33]. In many practical scenes, GI is subject to interference from the transmission medium and from optical background noise.…”
Section: Introductionmentioning
confidence: 99%
“…To quantitatively assess the quality of the reconstructed images, we adopt two metrics, PSNR and SSIM [52], which can be calculated with…”
Section: Simulation Resultsmentioning
confidence: 99%