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Related Concept Videos

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...
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...
Lossy Lines and Overvoltages01:22

Lossy Lines and Overvoltages

Transmission-line series resistance and shunt conductance cause three primary effects: attenuation, distortion, and power losses.
Attenuation
When constant series resistance and shunt conductance are present, voltage and current equations are modified. The propagation constant indicates that voltage and current waves consist of both forward and backward traveling components. These waves attenuate as they propagate, with the attenuation factor related to the resistance and conductance. In a...
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...
Downsampling01:20

Downsampling

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...
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...

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Feature-based wavelet shrinkage algorithm for image denoising.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2005
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Related Experiment Videos

Integer computation of lossy JPEG2000 compression.

Eric J Balster, Benjamin T Fortener, William F Turri

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |February 18, 2011
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an integer-based JPEG2000 compression engine using the Cohen-Daubechies-Feauvea (CDF) 9/7 wavelet transform and integer quantization. This method achieves comparable compression performance with significant reductions in computational complexity.

    Related Experiment Videos

    Area of Science:

    • Digital image processing
    • Wavelet transforms
    • Lossy compression algorithms

    Background:

    • The JPEG2000 standard enables efficient image compression using wavelet transforms.
    • Previous implementations often involve floating-point arithmetic, increasing computational complexity.
    • Integer-based computations are desirable for embedded systems and performance optimization.

    Discussion:

    • This paper presents an integer-based implementation of the Cohen-Daubechies-Feauvea (CDF) 9/7 wavelet transform for JPEG2000 compression.
    • The integration of integer transform and quantization allows for a fully integer computation pipeline.
    • This approach simplifies implementation and reduces computational overhead, particularly for embedded applications.

    Key Insights:

    • The integer-based CDF 9/7 wavelet transform and quantization achieve rate/distortion performance equivalent to the JasPer JPEG2000 engine.
    • A 30% reduction in wavelet transform computation time was observed.
    • Quantization processing time was reduced by an average of 56%.

    Outlook:

    • Further optimization of integer wavelet transforms for various compression standards.
    • Exploration of hardware acceleration for integer-based image compression.
    • Application of this integer computation method in real-time video compression and other multimedia processing tasks.