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Related Concept Videos

Reducing Line Loss01:18

Reducing Line Loss

223
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...
223
Lossless Lines01:23

Lossless Lines

193
In electrical engineering, a lossless transmission line is characterized by a purely imaginary propagation constant and a resistive characteristic impedance. The ABCD parameters, which describe the relationship between the input and output voltages and currents, indicate an equivalent π circuit with an imaginary series impedance and a shunt admittance. This results in a transmission line that, when the product of the phase constant (beta) and the length of the line is less than pi,...
193
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

193
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
193
Downsampling01:20

Downsampling

324
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
324
Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

181
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...
181
Upsampling01:22

Upsampling

364
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
364

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Related Experiment Video

Updated: Oct 22, 2025

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Spline-Based Dense Medial Descriptors for Lossy Image Compression.

Jieying Wang1, Jiří Kosinka1, Alexandru Telea2

  • 1Faculty of Science and Engineering, University of Groningen, 9747 AG Groningen, The Netherlands.

Journal of Imaging
|August 30, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces Spline-based Dense Medial Descriptors (SDMD) for image compression. The new method uses B-splines to represent medial descriptors, achieving higher compression ratios than JPEG with comparable image quality.

Keywords:
B-splinesimage compressionmedial descriptorssuper-resolution

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Area of Science:

  • Computer Vision
  • Image Processing
  • Geometric Modeling

Background:

  • Medial descriptors are crucial for image analysis tasks like simplification and compression.
  • B-splines are established tools for smooth curve representation in computer graphics.

Purpose of the Study:

  • To integrate medial descriptors with B-splines for enhanced image compression.
  • To develop an effective vector representation for raster images using B-spline medial descriptors.

Main Methods:

  • Modeling medial descriptors using stable and accurate B-splines.
  • Implementing the Spline-based Dense Medial Descriptors (SDMD) method.
  • Evaluating compression performance against established techniques like JPEG.

Main Results:

  • The SDMD method achieves significantly higher compression ratios compared to JPEG.
  • Image quality is maintained or improved with the SDMD method.
  • B-spline representation offers an effective vector format for raster images.

Conclusions:

  • Integrating B-splines with medial descriptors offers a powerful approach for image compression.
  • The SDMD method demonstrates superior performance and potential for applications like super-resolution and salient feature preservation.