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Related Concept Videos

Scaling01:26

Scaling

In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
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Phase Contrast and Differential Interference Contrast Microscopy

Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
Gain01:15

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Gain and phase shift are properties of linear circuits that describe the effect a circuit has on a sinusoidal input voltage or current. The circuit's behavior that contains reactive elements will depend on the frequency of the input sinusoid. As a result, it is observed that the gain and phase shift will all be frequency functions.
Gain:
Suppose Vin is the input and Vout is the output signal to a circuit.
Transfer function and Bode Plots-II01:23

Transfer function and Bode Plots-II

In the standard form, the transfer function is shown in constant gain, poles/zeros at origin, simple poles/zeros, and quadratic poles/zeros; each contributing uniquely to the system's overall response. The term represents the magnitude of the simple zero:

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Related Experiment Video

Updated: Jul 7, 2026

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

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Published on: January 28, 2019

Phase and magnitude in normalized images.

D Cochran1

  • 1Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1994
PubMed
Summary

Image information loss, whether phase or magnitude, causes distortion. For energy normalized images, phase information is more critical for preserving image structure under specific statistical assumptions.

Area of Science:

  • Image processing and analysis
  • Digital signal processing
  • Computer vision

Background:

  • Image reconstruction and analysis rely on both magnitude and phase information.
  • Complete loss or perturbation of either can lead to significant image distortion.
  • Energy normalization is a common preprocessing step in image analysis.

Purpose of the Study:

  • To investigate the impact of losing phase or magnitude information on energy normalized images.
  • To determine which type of information (phase or magnitude) is more crucial for image integrity.

Main Methods:

  • Mathematical analysis of image distortion models.
  • Consideration of energy normalized images.
  • Application of statistical assumptions on image structure.

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Last Updated: Jul 7, 2026

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Main Results:

  • Distortion is analyzed for complete loss or perturbation of phase or magnitude.
  • Under specific statistical assumptions, phase information loss causes greater distortion.
  • Phase information is demonstrated to be more critical for image reconstruction.

Conclusions:

  • Phase information plays a more vital role than magnitude information in maintaining the integrity of energy normalized images.
  • Understanding the differential importance of phase and magnitude is crucial for developing robust image processing algorithms.