Current Optics and Photonics

Optical Society of Korea (한국광학회)
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U2Net-based Single-pixel Imaging Salient Object Detection

  • Zhang, Leihong (College of Communication and Art design, University of Shanghai for Science and Technology) ;
  • Shen, Zimin (College of Communication and Art design, University of Shanghai for Science and Technology) ;
  • Lin, Weihong (College of Communication and Art design, University of Shanghai for Science and Technology) ;
  • Zhang, Dawei (School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology)
  • Received : 2022.04.15
  • Accepted : 2022.07.11
  • Published : 2022.10.25
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Abstract

At certain wavelengths, single-pixel imaging is considered to be a solution that can achieve high quality imaging and also reduce costs. However, achieving imaging of complex scenes is an overhead-intensive process for single-pixel imaging systems, so low efficiency and high consumption are the biggest obstacles to their practical application. Improving efficiency to reduce overhead is the solution to this problem. Salient object detection is usually used as a pre-processing step in computer vision tasks, mimicking human functions in complex natural scenes, to reduce overhead and improve efficiency by focusing on regions with a large amount of information. Therefore, in this paper, we explore the implementation of salient object detection based on single-pixel imaging after a single pixel, and propose a scheme to reconstruct images based on Fourier bases and use U2Net models for salient object detection.

Keywords

Acknowledgement

Natural Science Foundation of Shanghai (Grant No. 18ZR1425800); the National Natural Science Foundation of China (Grant No. 61775140, 61875125).

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