Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Curvilinear Motion: Rectangular Components

Curvilinear Motion: Rectangular Components

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 time...

Relative Motion Analysis using Rotating Axes-Problem Solving

Relative Motion Analysis using Rotating Axes-Problem Solving

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...

Relative Motion Analysis using Rotating Axes

Relative Motion Analysis using Rotating Axes

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 instrumental in...

Reconstruction of Signal using Interpolation

Reconstruction of Signal using Interpolation

Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next sampling...

Relative Motion Analysis using Rotating Axes - Acceleration

Relative Motion Analysis using Rotating Axes - Acceleration

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. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...

Rotation with Constant Angular Acceleration - II

Rotation with Constant Angular Acceleration - II

Kinematics is the description of motion. The kinematics of rotational motion discusses the relationships between rotation angle, angular velocity, angular acceleration, and time. One can describe many things with great precision using kinematics, but kinematics does not consider causes. For example, a large angular acceleration describes a very rapid change in angular velocity without any consideration of its cause. Thus, rotational kinematics does not represent the laws of nature.
The first...

You might also read

Related Articles

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

Sort by

Same author

Application of motion prediction based on a long short-term memory network for imaging dose reduction in real-time tumor-tracking radiation therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2024

Same author

Wavefront restoration from lateral shearing data using spectral interpolation.

Applied optics·2023

Same author

Technical Note: Range verification of pulsed proton beams from fixed-field alternating gradient accelerator by means of time-of-flight measurement of ionoacoustic waves.

Medical physics·2021

Same author

On-line range verification for proton beam therapy using spherical ionoacoustic waves with resonant frequency.

Scientific reports·2020

Same author

Correction to: Systolic modified Look-Locker inversion recovery myocardial T1 mapping improves the accuracy of T1 and extracellular volume fraction measurements of patients with high heart rate or atrial fibrillation.

Radiological physics and technology·2020

Same author

Systolic modified Look-Locker inversion recovery myocardial T1 mapping improves the accuracy of T1 and extracellular volume fraction measurements of patients with high heart rate or atrial fibrillation.

Radiological physics and technology·2020

Search research articles

Related Experiment Video

Updated: May 27, 2026

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Reliable phase unwrapping algorithm based on rotational and direct compensators.

Samia Heshmat¹, Satoshi Tomioka, Shusuke Nishiyama

¹Graduate School of Engineering, Hokkaido University, Kita-ku, Sapporo, Japan. samia@athena.qe.eng.hokudai.ac.jp

|November 24, 2011

Summary

This study presents a novel phase unwrapping method for noisy data, improving accuracy and speed. The rotational compensator (RC) approach enhances processing of continuous objects by compensating phase discontinuities.

More Related Videos

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

Related Experiment Videos

Last Updated: May 27, 2026

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

Published on: July 5, 2016

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

Area of Science:

Image processing
Signal processing
Computational physics

Background:

Phase unwrapping is crucial for data processing involving phase information.
Existing methods face challenges with noisy data and computational efficiency.

Purpose of the Study:

To introduce a new, efficient phase unwrapping algorithm for noisy wrapped phase maps.
To improve accuracy and reduce computational time in phase unwrapping.

Main Methods:

A novel phase unwrapping approach utilizing a rotational compensator (RC) method.
Compensation of discontinuity sources, including direct compensation for adjoining singular point (SP) pairs and RC for other SP pairs.

Main Results:

The proposed algorithm demonstrates improved accuracy and computational efficiency compared to existing methods.
Tested successfully on both simulated and real-world noisy wrapped phase data.
Faster than the original rotational compensator (RC) algorithm.

Conclusions:

The new phase unwrapping method offers a significant advancement for processing noisy phase data.
The algorithm provides a more accurate and computationally efficient solution for continuous objects.