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Related Concept Videos

Bandpass Sampling01:17

Bandpass Sampling

In signal processing, bandpass sampling is an effective technique for sampling signals that have most of their energy concentrated within a narrow frequency band. This type of signal is known as a bandpass signal. The key principle of bandpass sampling involves sampling the signal at a rate that is greater than twice the signal's bandwidth to prevent aliasing.
A bandpass signal has a spectrum with a lower frequency limit, denoted as ω1, and an upper frequency limit, denoted as ω2. The spectrum...
Properties of Fourier series II01:21

Properties of Fourier series II

Time scaling of signals is a crucial concept in signal processing that affects the Fourier series representation without altering its coefficients. The process modifies the fundamental frequency, thereby changing how the series represents the signal over time. This principle is essential in various applications, including audio and image processing, where signal manipulation is frequent. Understanding function symmetries is fundamental to simplifying the Fourier series.
A function f(t) is...
Upsampling01:22

Upsampling

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...
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.
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...
Properties of Fourier series I01:20

Properties of Fourier series I

The Fourier series is a powerful tool in signal processing and communications, allowing periodic signals to be expressed as sums of sine and cosine functions. A foundational property of the Fourier series is linearity. If we consider two periodic signals, their linear combination results in a new signal whose Fourier coefficients are simply the corresponding linear combinations of the original signals' coefficients. This property is crucial in applications like frequency modulation (FM) radio,...

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Related Experiment Video

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Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

A development of symmetric extension method for subband image coding.

H Kiya1, K Nishikawa, M Iwahashi

  • 1Fac. of Technol., Tokyo Metropolitan Univ.

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

This study introduces a symmetric extension method for subband image coding, enhancing coding quality. The technique removes prior restrictions by analyzing symmetrically extended signals, broadening its applications.

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Area of Science:

  • Digital image processing
  • Signal processing
  • Data compression

Background:

  • Subband image coding techniques are essential for efficient image compression.
  • Existing methods, like the symmetric extension method, face restrictions limiting their applicability.
  • These restrictions stem from the nature of symmetrically extended signals during the analysis phase.

Purpose of the Study:

  • To develop an improved symmetric extension method for subband image coding.
  • To overcome the limitations of existing symmetric extension techniques.
  • To enhance the quality and applicability of subband image coding.

Main Methods:

  • Development of a novel symmetric extension technique for subband image coding.
  • Analysis of the properties of symmetrically extended signals.
  • Examination and formulation of signal behavior after filtering and decimation processes.

Main Results:

  • The developed technique achieves high-quality image coding.
  • Restrictions associated with previous subband coding systems are successfully removed.
  • The method's applicability is extended to a wider range of scenarios.

Conclusions:

  • The enhanced symmetric extension method offers superior performance in subband image coding.
  • This advancement removes previous limitations, making the technique more versatile.
  • The developed approach contributes to more efficient and higher-quality image compression.