Compressive sensing ghost imaging based on image gradient

Chen, Yi; Cheng, Zhengdong; Fan, Xin; Yu-bao, Cheng; Liang, Zhenyu

doi:10.1016/j.ijleo.2019.01.067

Cited by 18 publications

(5 citation statements)

References 21 publications

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“…In addition, with the buttress of the results offered in our work, it is possible to combine the compressive sensing with pink noise CGI, which might further decrease the total required number of sampling without losing the quality of results [28,29]. On the other hand, due to the cross-correlation, a low level of edge's sharpness is main disadvantage of pink noise CGI.…”

Section: Discussionmentioning

confidence: 78%

Moving Object Captured with Pink Noise Pattern in Computational Ghost Imaging

Nie¹,

Zhao²,

Peng³

et al. 2020

Preprint

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We develop and experimentally demonstrate an imaging method based on the pink noise pattern in the computational ghost imaging (CGI) system, which has a strong ability to photograph moving objects. To examine its unique ability and scope of application, the object oscillates with variable amplitude in horizontal axis, and the result via commonly used white noise are also measured as a comparison. We show that our method can image the object when the white noise method fails. In addition, our method uses less number of patterns, and enhances the signal-to-noise ratio (SNR) to a great extent.

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Section: Discussionmentioning

confidence: 78%

Moving Object Captured with Pink Noise Pattern in Computational Ghost Imaging

Nie¹,

Zhao²,

Peng³

et al. 2020

Preprint

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“…Here, two phase modulated masks, M1 and M2, are illuminated with a coherent source of light and interfered to obtain the final encrypted image in the output plane. Ghost imaging, on the other hand, involves capturing information through correlated intensity measurements of entangled photon pairs, providing a novel means of encryption that leverages quantum properties [104][105][106][107][108][109][110][111][112][113]. Holography-based encryption relies on the creation and reconstruction of holograms to encode and decode information [114][115][116][117][118][119][120][121][122][123].…”

Section: Other Optical Encryption Algorithmsmentioning

confidence: 99%

Advances in Optical Visual Information Security: A Comprehensive Review

Sachin,

Kumar,

Sakshi

et al. 2024

Photonics

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In the modern era, the secure transmission and storage of information are among the utmost priorities. Optical security protocols have demonstrated significant advantages over digital counterparts, i.e., a high speed, a complex degree of freedom, physical parameters as keys (i.e., phase, wavelength, polarization, quantum properties of photons, multiplexing, etc.) and multi-dimension processing capabilities. This paper provides a comprehensive overview of optical cryptosystems developed over the years. We have also analyzed the trend in the growth of optical image encryption methods since their inception in 1995 based on the data collected from various literature libraries such as Google Scholar, IEEE Library and Science Direct Database. The security algorithms developed in the literature are focused on two major aspects, i.e., symmetric and asymmetric cryptosystems. A summary of state-of-the-art works is described based on these two aspects. Current challenges and future perspectives of the field are also discussed.

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“…• Case 1: sparse structure is expected in a transform domain such as the DCT. The inverse transform matrix represents the 2D inverse DCT, applied to the minimization outcome to obtain the reconstructed two-dimensional image • Case 2a: as well-known from previous works [39][40][41], the discrete gradient of natural images along the horizontal and vertical directions are sparse, therefore TV regularization can be used, as firstly proposed by Rudin-Osher-Fatemi [42].…”

Section: Compressive Correlation Plenoptic Imagingmentioning

confidence: 99%

Compressive sensing-based correlation plenoptic imaging

Petrelli,

Santoro,

Massaro

et al. 2023

Front. Phys.

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Correlation Plenoptic Imaging (CPI) is an innovative approach to plenoptic imaging that tackles the inherent trade-off between image resolution and depth of field. By exploiting the intensity correlations that characterize specific states of light, it extracts information of the captured light direction, enabling the reconstruction of images with increased depth of field while preserving resolution. We describe a novel reconstruction algorithm, relying on compressive sensing (CS) techniques based on the discrete cosine transform and on gradients, used in order to reconstruct CPI images with a reduced number of frames. We validate the algorithm using simulated data and demonstrate that CS-based reconstruction techniques can achieve high-quality images with smaller acquisition times, thus facilitating the practical application of CPI.

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Compressive sensing ghost imaging based on image gradient

Cited by 18 publications

References 21 publications

Moving Object Captured with Pink Noise Pattern in Computational Ghost Imaging

Moving Object Captured with Pink Noise Pattern in Computational Ghost Imaging

Advances in Optical Visual Information Security: A Comprehensive Review

Compressive sensing-based correlation plenoptic imaging

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