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Relative Motion Analysis using Rotating Axes01:25

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...
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been developed.
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

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 drone...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

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...
Curvilinear Motion: Rectangular Components01:23

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 - Acceleration01:22

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...

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Related Experiment Video

Updated: Jul 19, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

An improved observation model for super-resolution under affine motion.

Gilles Rochefort1, Frédéric Champagnat, Guy Le Besnerais

  • 1Office National d'Etudes et de Recherches Aérospatiales, 92322 Chatillon, France, France. grochefort@realeyes3d.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|November 2, 2006
PubMed
Summary

This study introduces a new super-resolution (SR) observation model for non-isometric motion, improving image resolution from sequences with varying scales. The model enhances airborne imaging sensor data effectively.

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Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
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Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Published on: December 1, 2016

Related Experiment Videos

Last Updated: Jul 19, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)
11:57

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM)

Published on: December 1, 2016

Area of Science:

  • Computer Vision
  • Image Processing
  • Remote Sensing

Background:

  • Super-resolution (SR) techniques enhance image resolution using subpixel shifts.
  • Existing SR models often assume isometric motion, limiting their application in scenarios like airborne imaging.

Purpose of the Study:

  • To propose an original observation model for SR that accommodates non-isometric inter-frame motion.
  • To extend existing SR observation models to handle affine motion, particularly for airborne imaging sensors.

Main Methods:

  • Reviewed existing SR observation models and their limitations with non-isometric motion.
  • Extended the Elad and Feuer observation model to handle affine motion by decomposing affine transforms into shear transforms.
  • Implemented the model using efficient one-dimensional affine transforms.

Main Results:

  • Demonstrated improved SR reconstruction results on synthetic and real image sequences with variable scale motions.
  • Achieved comparable results to existing methods in cases of isometric motion.
  • Validated the model's effectiveness for airborne imaging sensor applications.

Conclusions:

  • The proposed observation model effectively handles non-isometric affine motion in SR.
  • This advancement is particularly beneficial for applications like airborne imaging where motion is often non-isometric.
  • The method offers enhanced performance for variable scale motions while maintaining parity for isometric ones.