An Edge Detection Model Based on W-Transform Single Pixel Imaging

Guangyao Chen; Yuanping Xu; Chao Kong; Zhijie Xu; Yanlong Cao; Kaiwei Wang; Chaolong Zhang

doi:10.1109/ICOIM60566.2023.10491524

An Edge Detection Model Based on W-Transform Single Pixel Imaging

Guangyao Chen, Yuanping Xu^*, Chao Kong, Zhijie Xu, Yanlong Cao, Kaiwei Wang, Chaolong Zhang

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

Abstract

To efficiently reduce the required measurement count for single-pixel imaging edge detection, this study devises an edge detection model based on W-transform single-pixel imaging. In this model, the convolution of the DoG (Difference of Gaussians) operator and W-transform basis patterns as modulation patterns are employed to directly extract edge information from the spectral domain of the target object. Different from traditional methods, it achieves the extraction of edge details from an object without imaging. Numerical simulations and experimental results demonstrate that this model extracts edges with higher signal-to-noise ratios compared to the edge extraction using phase-shifted sinusoidal patterns. Additionally, the proposed model reduces the number of modulation patterns required by half, so as to gain double efficiency. The integration of W-transform single-pixel imaging with edge detection offers a novel approach for edge detections without the need for imaging.

Original language	English
Title of host publication	2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	51-55
Number of pages	5
ISBN (Electronic)	9798350358636
DOIs	https://doi.org/10.1109/ICOIM60566.2023.10491524
Publication status	Published - 2023
Externally published	Yes
Event	2nd International Conference on Optical Imaging and Measurement, ICOIM 2023 - Hybrid, Xi�an, China Duration: 20 Oct 2023 → 22 Oct 2023

Publication series

Name	2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023

Conference

Conference	2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
Country/Territory	China
City	Hybrid, Xi�an
Period	20/10/23 → 22/10/23

Keywords

DoG
Edge Detection
non-imaging
Single-pixel imaging
W-transform

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10.1109/ICOIM60566.2023.10491524

Cite this

Chen, G., Xu, Y., Kong, C., Xu, Z., Cao, Y., Wang, K., & Zhang, C. (2023). An Edge Detection Model Based on W-Transform Single Pixel Imaging. In 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023 (pp. 51-55). (2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICOIM60566.2023.10491524

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title = "An Edge Detection Model Based on W-Transform Single Pixel Imaging",

abstract = "To efficiently reduce the required measurement count for single-pixel imaging edge detection, this study devises an edge detection model based on W-transform single-pixel imaging. In this model, the convolution of the DoG (Difference of Gaussians) operator and W-transform basis patterns as modulation patterns are employed to directly extract edge information from the spectral domain of the target object. Different from traditional methods, it achieves the extraction of edge details from an object without imaging. Numerical simulations and experimental results demonstrate that this model extracts edges with higher signal-to-noise ratios compared to the edge extraction using phase-shifted sinusoidal patterns. Additionally, the proposed model reduces the number of modulation patterns required by half, so as to gain double efficiency. The integration of W-transform single-pixel imaging with edge detection offers a novel approach for edge detections without the need for imaging.",

keywords = "DoG, Edge Detection, non-imaging, Single-pixel imaging, W-transform",

author = "Guangyao Chen and Yuanping Xu and Chao Kong and Zhijie Xu and Yanlong Cao and Kaiwei Wang and Chaolong Zhang",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023 ; Conference date: 20-10-2023 Through 22-10-2023",

year = "2023",

doi = "10.1109/ICOIM60566.2023.10491524",

language = "English",

series = "2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023",

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Chen, G, Xu, Y, Kong, C, Xu, Z, Cao, Y, Wang, K & Zhang, C 2023, An Edge Detection Model Based on W-Transform Single Pixel Imaging. in 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023. 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023, Institute of Electrical and Electronics Engineers Inc., pp. 51-55, 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023, Hybrid, Xi�an, China, 20/10/23. https://doi.org/10.1109/ICOIM60566.2023.10491524

An Edge Detection Model Based on W-Transform Single Pixel Imaging. / Chen, Guangyao; Xu, Yuanping; Kong, Chao et al.
2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 51-55 (2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

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AU - Chen, Guangyao

AU - Xu, Yuanping

AU - Kong, Chao

AU - Xu, Zhijie

AU - Cao, Yanlong

AU - Wang, Kaiwei

AU - Zhang, Chaolong

PY - 2023

Y1 - 2023

N2 - To efficiently reduce the required measurement count for single-pixel imaging edge detection, this study devises an edge detection model based on W-transform single-pixel imaging. In this model, the convolution of the DoG (Difference of Gaussians) operator and W-transform basis patterns as modulation patterns are employed to directly extract edge information from the spectral domain of the target object. Different from traditional methods, it achieves the extraction of edge details from an object without imaging. Numerical simulations and experimental results demonstrate that this model extracts edges with higher signal-to-noise ratios compared to the edge extraction using phase-shifted sinusoidal patterns. Additionally, the proposed model reduces the number of modulation patterns required by half, so as to gain double efficiency. The integration of W-transform single-pixel imaging with edge detection offers a novel approach for edge detections without the need for imaging.

AB - To efficiently reduce the required measurement count for single-pixel imaging edge detection, this study devises an edge detection model based on W-transform single-pixel imaging. In this model, the convolution of the DoG (Difference of Gaussians) operator and W-transform basis patterns as modulation patterns are employed to directly extract edge information from the spectral domain of the target object. Different from traditional methods, it achieves the extraction of edge details from an object without imaging. Numerical simulations and experimental results demonstrate that this model extracts edges with higher signal-to-noise ratios compared to the edge extraction using phase-shifted sinusoidal patterns. Additionally, the proposed model reduces the number of modulation patterns required by half, so as to gain double efficiency. The integration of W-transform single-pixel imaging with edge detection offers a novel approach for edge detections without the need for imaging.

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Chen G, Xu Y, Kong C, Xu Z, Cao Y, Wang K et al. An Edge Detection Model Based on W-Transform Single Pixel Imaging. In 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 51-55. (2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023). doi: 10.1109/ICOIM60566.2023.10491524

An Edge Detection Model Based on W-Transform Single Pixel Imaging

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