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Related Concept Videos

Traveling Waves: Lossless Lines01:27

Traveling Waves: Lossless Lines

The provided content explores the behavior of traveling waves on single-phase lossless transmission lines. It begins with a single-phase two-wire lossless transmission line of length Δx, characterized by a loop inductance LH/m and a line-to-line capacitance C F/m. These parameters result in a series inductance LΔx and a shunt capacitance CΔx.
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...
Lossless Lines01:23

Lossless Lines

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, exhibits...
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...
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...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

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.

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Related Experiment Videos

Integer wavelet transform for embedded lossy to lossless image compression.

J Reichel1, G Menegaz, M J Nadenau

  • 1Signal Processing Laboratory, Swiss Federal Institute of Technology, 1015 Lausanne, Switzerland. reichel@ieee.org

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
Summary
This summary is machine-generated.

The integer wavelet transform (IWT) offers similar compression performance to the discrete wavelet transform (DWT) for lossy image compression. This study models IWT

Related Experiment Videos

Area of Science:

  • Digital Image Processing
  • Signal Processing
  • Data Compression

Background:

  • Discrete Wavelet Transform (DWT) is a standard for embedded lossy image compression.
  • Lifting Scheme (LS) enables perfect reconstruction and nonlinear transforms, leading to Integer Wavelet Transform (IWT) for efficient lossless compression.
  • IWT presents an alternative to DWT with comparable rate-distortion performance.

Purpose of the Study:

  • To theoretically investigate and model the degradations introduced by using IWT instead of DWT in lossy image compression.
  • To analyze the impact of rounding operations in IWT on reconstructed image quality.

Main Methods:

  • Developed a theoretical framework to model degradations caused by IWT in lossy compression.
  • Modeled rounding operations in IWT as additive noise.
  • Propagated the modeled noise through the Lifting Scheme structure to assess its impact on reconstructed pixels.

Main Results:

  • The proposed noise propagation model accurately predicts results obtained with the EZW algorithm for image compression using IWT.
  • Experimental comparisons quantified differences in bit rate and visual quality between IWT and DWT for lossy compression.

Conclusions:

  • The study provides a theoretical understanding of IWT's impact on lossy image compression quality.
  • The developed model aids in predicting and managing compression artifacts introduced by IWT.