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Related Concept Videos

Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
Reconstruction of Signal using Interpolation01:10

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...
Aliasing01:18

Aliasing

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 signal...
Reducing Line Loss01:18

Reducing Line Loss

In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss in...

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Related Experiment Video

Updated: May 14, 2026

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

Accelerated edge-preserving image restoration without boundary artifacts.

Antonios Matakos1, Sathish Ramani, Jeffrey A Fessler

  • 1Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA. amatakos@umich.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2013
PubMed
Summary

This study introduces a novel image restoration method to eliminate wraparound artifacts caused by circulant blur models. The technique efficiently suppresses noise and preserves edges, improving boundary image quality.

Related Experiment Videos

Last Updated: May 14, 2026

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

Area of Science:

  • Image restoration
  • Computational imaging
  • Signal processing

Background:

  • Nonquadratic regularizers like l1 and total-variation suppress noise while preserving edges in image restoration.
  • Circulant blur models, common in image restoration, can cause boundary artifacts due to periodicity.
  • Noncirculant models avoid artifacts but increase computational complexity.

Purpose of the Study:

  • To develop an efficient image restoration method that prevents wraparound artifacts from circulant blur models.
  • To combine the benefits of circulant models (efficiency) with noncirculant models (artifact prevention).
  • To handle various convex regularizers, including edge-preserving and sparsity-promoting ones.

Main Methods:

  • A circulant blur model is combined with a masking operator to prevent wraparound artifacts.
  • An efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies is proposed.
  • Alternating minimization and fast Fourier transforms (FFTs) enable noniterative solutions to linear systems.

Main Results:

  • The proposed method effectively prevents wraparound artifacts at image boundaries.
  • Fast convergence and improved image quality, especially at boundaries, were demonstrated through simulations.
  • The algorithm efficiently handles diverse convex regularizers like total-variation and l1-norm.

Conclusions:

  • The proposed masking operator with a circulant blur model effectively mitigates boundary artifacts in image restoration.
  • The efficient algorithm utilizing variable splitting and AL strategies offers a computationally advantageous solution.
  • This approach enhances image quality at boundaries without sacrificing the ability to use various regularizers.