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 proceedingConference Proceedingpeer-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 languageEnglish
Title of host publication2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages51-55
Number of pages5
ISBN (Electronic)9798350358636
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2nd International Conference on Optical Imaging and Measurement, ICOIM 2023 - Hybrid, Xi�an, China
Duration: 20 Oct 202322 Oct 2023

Publication series

Name2023 2nd International Conference on Optical Imaging and Measurement, ICOIM 2023

Conference

Conference2nd International Conference on Optical Imaging and Measurement, ICOIM 2023
Country/TerritoryChina
CityHybrid, Xi�an
Period20/10/2322/10/23

Keywords

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

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