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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
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Underwater Object Detection and Reconstruction Based on Active Single-Pixel Imaging and Super-Resolution

Mengdi Li1,2, Anumol Mathai2, Stephen L H Lau2

  • 1College of Optoelectronic Engineering, Changchun University of Science and Technology, Changchun 130022, China.

Sensors (Basel, Switzerland)
|January 20, 2021
PubMed
Summary

This study introduces a novel single-pixel imaging (SPI) system using compressive sensing super-resolution convolutional neural network (CS-SRCNN) for clearer underwater object inspection. The CS-SRCNN method significantly improves image quality, offering a better alternative for underwater optical imaging.

Keywords:
compressive sensingsingle-pixel imagingsuper-resolution convolutional neural network

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Area of Science:

  • Optical Engineering
  • Image Processing
  • Underwater Technology

Background:

  • Underwater imaging is challenging due to light scattering and absorption.
  • Single-pixel imaging (SPI) offers a potential solution for low-light conditions.

Purpose of the Study:

  • To develop an improved single-pixel imaging system for underwater object inspection.
  • To enhance image reconstruction quality using a novel algorithm.

Main Methods:

  • Implementation of a single-pixel object inspection system for underwater environments.
  • Application of a compressive sensing super-resolution convolutional neural network (CS-SRCNN) algorithm.
  • Investigation of compression ratios and analysis of peak signal to noise ratio (PSNR) and structural similarity index (SSIM).

Main Results:

  • Successful image reconstruction using only 30% of total pixels with CS-SRCNN.
  • Significant improvements in PSNR (35.44%) and SSIM (73.07%) compared to existing methods.
  • Demonstrated efficiency of the proposed method over standard SPI and SRCNN.

Conclusions:

  • The CS-SRCNN based SPI system provides a high-quality imaging solution for underwater objects.
  • This research offers new insights into SPI applications in challenging underwater environments.
  • The proposed method presents a superior alternative for underwater optical object imaging.