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The speed of sound in a gaseous medium depends on various factors. Since gases constitute molecules that are free to move, they are highly compressible. Hence, sound waves travel slowly through gases. Thermodynamics helps us understand the relationship between pressure, volume, and temperature of gases, thus, the speed of sound in an ideal gas can be determined using the laws of thermodynamics. At the same time, Newton's laws of motion and the continuity equation of fluid dynamics also come...
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Related Experiment Video

Updated: Feb 10, 2026

Imaging and Quantification of the Area of Fast-Moving Microbubbles Using a High-Speed Camera and Image Analysis
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A High-Speed Imaging Method Based on Compressive Sensing for Sound Extraction Using a Low-Speed Camera.

Ge Zhu1, Xu-Ri Yao2, Zhi-Bin Sun3,4

  • 1Center for Quantum Technology Research, School of Physics, Beijing Institute of Technology, Beijing 100081, China. 2120111573@bit.edu.cn.

Sensors (Basel, Switzerland)
|May 13, 2018
PubMed
Summary

This study presents a compressive sensing method to reconstruct high-speed videos from low-speed camera footage, enabling efficient sound extraction from light spot vibrations. This technique achieves a 20x speed improvement for capturing dynamic events.

Keywords:
compressive sensingcomputational imaginghigh-speed imagingremote sensingsound recoveryvibration analysis

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Last Updated: Feb 10, 2026

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Area of Science:

  • Optics and Photonics
  • Acoustics
  • Signal Processing

Background:

  • High-speed imaging is crucial for analyzing dynamic phenomena.
  • Traditional high-speed cameras are often expensive and have limitations.
  • Compressive sensing offers a potential solution for reconstructing high-speed data from limited samples.

Purpose of the Study:

  • To develop an efficient method for sound extraction using high-speed light spot videos.
  • To reconstruct high-speed videos from low-speed captured images via compressive sensing.
  • To validate the method's effectiveness through simulations and experiments.

Main Methods:

  • Utilizing a low-speed charge-coupled device (CCD) camera modulated by a digital micro-mirror device (DMD).
  • Reconstructing high-speed light spot videos (2000 Hz) from low-speed (100 Hz) captures.
  • Employing light spot centroid analysis to recover sound vibrations.

Main Results:

  • Achieved a 20x speed improvement in video reconstruction.
  • Successfully recovered speech with an intelligibility value of 0.8185.
  • Evaluated the impact of synchronization, sampling patterns, and vibration amplitudes.

Conclusions:

  • The compressive sensing method enables efficient sound extraction from high-speed light spot videos.
  • The technique offers a significant speed enhancement over conventional methods.
  • Potential applications extend to vibration and motion analysis beyond sound detection.