TY - GEN
T1 - An Edge Detection Model Based on W-Transform Single Pixel Imaging
AU - Chen, Guangyao
AU - Xu, Yuanping
AU - Kong, Chao
AU - Xu, Zhijie
AU - Cao, Yanlong
AU - Wang, Kaiwei
AU - Zhang, Chaolong
N1 - Publisher Copyright:
© 2023 IEEE.
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.
KW - DoG
KW - Edge Detection
KW - non-imaging
KW - Single-pixel imaging
KW - W-transform
UR - http://www.scopus.com/inward/record.url?scp=85191322463&partnerID=8YFLogxK
U2 - 10.1109/ICOIM60566.2023.10491524
DO - 10.1109/ICOIM60566.2023.10491524
M3 - Conference Proceeding
AN - SCOPUS:85191322463
T3 - 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
SP - 51
EP - 55
BT - 2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
Y2 - 20 October 2023 through 22 October 2023
ER -