Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

742
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
742
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

1.0K
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
1.0K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

834
Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
834
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.6K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
1.6K
Deconvolution01:20

Deconvolution

764
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
764
Aliasing01:18

Aliasing

934
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
934

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Permanent Pacemaker Implantation After Minimally Invasive Robotic Cardiac Surgery and Long-Term Pacemaker Dependence Rates.

Anatolian journal of cardiology·2026
Same author

Reply to the Letter to the Editor: "Stiffness or Reflection? A Critical Appraisal of Energy Drink Induced Vascular Changes".

Anatolian journal of cardiology·2026
Same author

Association of Treadmill Exercise Testing Parameters with PREVENT-Estimated Cardiovascular Risk: A Cross-Sectional Analysis.

Journal of clinical medicine·2026
Same author

The effect of different initial solutions on the metaheuristic algorithms for the single allocation p-hub center and routing problem.

PeerJ. Computer science·2025
Same author

Detection and classification of femoral neck fractures from plain pelvic X-rays using deep learning and machine learning methods.

Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES·2025
Same author

Evaluating the Acute Effects of Energy Drink Consumption on Arterial Stiffness in Healthy Young Adults.

Anatolian journal of cardiology·2025

Related Experiment Video

Updated: Apr 24, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K

IMU-aided adaptive mesh-grid based video motion deblurring.

Ahmet Arslan1, Gokhan Koray Gultekin2, Afsar Saranli3

  • 1Center for Image Analysis (OGAM), Middle East Technical University, Ankara, Turkey.

Peerj. Computer Science
|December 9, 2024
PubMed
Summary

This study introduces an adaptive mesh-grid algorithm for motion deblurring, effectively handling non-uniform blur. The new method improves image quality and reduces computation time compared to existing techniques.

Keywords:
Blur kernelCamerasImage restorationInertial measurement unitMotion deblurringNon-uniform motion blurPoint spread function

More Related Videos

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

Published on: February 8, 2014

12.2K
Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

533

Related Experiment Videos

Last Updated: Apr 24, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

15.6K
Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

Published on: February 8, 2014

12.2K
Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing
06:25

Author Spotlight: Assessment of Visual Acuity in Central Vision Loss Through Motion-Based Peripheral Vision Testing

Published on: February 23, 2024

533

Area of Science:

  • Computer Vision
  • Image Processing
  • Computational Photography

Background:

  • Motion blur degrades image quality and hinders computer vision tasks.
  • Existing deblurring algorithms primarily address uniform blur, failing with non-uniform motion.
  • Non-uniform motion blur presents a significant challenge in image restoration.

Purpose of the Study:

  • To develop a novel motion deblurring algorithm for non-uniform blur.
  • To reduce computational cost while improving deblurring performance.
  • To introduce an adaptive mesh-grid approach for managing complex motion blur.

Main Methods:

  • An adaptive mesh-grid approach is proposed to manage non-uniform motion blur.
  • The image is divided into adaptive-sized grid cells based on blur variance.
  • Blur point spread function (PSF) is estimated using inertial sensor data.
  • A metric for in-frame spatial variance of blur magnitude is introduced.

Main Results:

  • The adaptive mesh-size algorithm enhances spatial accuracy of PSF estimation.
  • Experiments show a 5% increase in Peak Signal-to-Noise Ratio (PSNR) gain.
  • Average computation time decreased by 19% compared to constant mesh-size methods.
  • Two algorithm versions are studied: one for quality, one for balanced performance.

Conclusions:

  • The proposed adaptive mesh-grid algorithm effectively addresses non-uniform motion blur.
  • The method offers improved image quality and computational efficiency.
  • The adaptive approach provides flexibility for different application requirements.