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Related Concept Videos

Group Polarization01:01

Group Polarization

Group polarization is the strengthening of an original group attitude following the discussion of views within a group (Teger & Pruitt, 1967). That is, if a group initially favors a viewpoint, after discussion the group consensus is likely a stronger endorsement of the viewpoint. Conversely, if the group was initially opposed to a viewpoint, group discussion would likely lead to stronger opposition.
Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)01:15

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT)

Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) is an advanced Nuclear Magnetic Resonance (NMR) technique specifically designed to detect and enhance the signals of low-abundance nuclei, such as carbon-13 and nitrogen-15, in small molecules. The fundamental principle behind INEPT is the transfer of polarization from a more abundant and highly polarizable nucleus, typically hydrogen-1, to the low-abundance nucleus of interest. This process effectively boosts the NMR signal of the...
Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position with respect to time...
Polar Coordinates01:24

Polar Coordinates

The polar coordinate system offers an alternative to the Cartesian coordinate system for specifying points in a plane, using a distance and an angle instead of x and y coordinates. This system is particularly advantageous in situations involving circular or rotational symmetry, such as in physics or engineering problems involving waves, oscillations, or orbital paths.Defining Polar CoordinatesIn polar coordinates, a point is represented as P(r, ��), where r is the radial distance from a fixed...
Transformations of Functions III01:20

Transformations of Functions III

Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...

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Related Experiment Video

Updated: Jun 4, 2026

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Inversion by P4: polarization-picture post-processing.

Yoav Y Schechner1

  • 1Department of Electrical Engineering, Technion, Israel Institute of Technology, Haifa 32000, Israel. yoav@ee.technion.ac.il

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|February 2, 2011
PubMed
Summary
This summary is machine-generated.

This study presents a physics-based approach to polarization-picture post-processing (P(4)) for enhanced scene understanding. It models polarization data as an inverse problem, enabling applications like haze removal and 3D recovery.

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Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser

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Last Updated: Jun 4, 2026

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser
09:00

Experimental Methods for Spin- and Angle-Resolved Photoemission Spectroscopy Combined with Polarization-Variable Laser

Published on: June 28, 2018

Area of Science:

  • Computer Vision
  • Biological Imaging
  • Optical Engineering

Background:

  • Polarization sensing is utilized in both engineered and biological systems.
  • Polarization data often serves as a cue for scene information recovery, not a direct variable.
  • Effective polarization-picture post-processing (P(4)) is crucial for advanced scene understanding.

Purpose of the Study:

  • To determine optimal polarization-picture post-processing (P(4)) methods for superior scene understanding.
  • To bridge advanced computer vision techniques with biological polarization sensing hypotheses.
  • To frame scene recovery using polarization as an inverse problem.

Main Methods:

  • Developing a physics-based model incorporating polarization components for scene recovery.
  • Applying inversion techniques to polarization data.
  • Utilizing signal-processing methods like independent component analysis, deconvolution, and optimization.

Main Results:

  • Demonstrated automatic removal of path radiance in challenging conditions (haze, underwater).
  • Enabled overcoming of partial semi-reflections and visual reverberations.
  • Facilitated three-dimensional scene recovery and distance-adaptive denoising.

Conclusions:

  • A principled inverse problem approach using physics-based models significantly enhances scene understanding from polarization data.
  • This methodology offers practical solutions for engineering challenges and insights into biological visual processing.
  • The developed inversion algorithms are versatile and effective for various image restoration and recovery tasks.