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Related Concept Videos

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...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
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...
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...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
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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.
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Related Experiment Video

Updated: May 24, 2026

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

Efficient rate-distortion optimal packetization of embedded bitstreams into independent source packets.

Sorina Dumitrescu1, Jiayi Xu

  • 1Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada. sorina@mail.ece.mcmaster.ca

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 16, 2012
PubMed
Summary

This study introduces a fast algorithm for rate-distortion optimal packetization (RDOP) of embedded image bitstreams. It significantly reduces processing time for transmitting images over noisy channels, minimizing distortion.

Related Experiment Videos

Last Updated: May 24, 2026

Quasi-light Storage for Optical Data Packets
07:45

Quasi-light Storage for Optical Data Packets

Published on: February 6, 2014

Area of Science:

  • Digital image processing
  • Information theory
  • Computer vision

Background:

  • Image transmission over packet networks is prone to errors.
  • Embedded bitstreams require efficient packetization to mitigate error propagation.
  • Existing methods for rate-distortion optimal packetization (RDOP) have computational limitations.

Purpose of the Study:

  • To extend the rate-distortion optimal packetization (RDOP) problem formulation to include minimization of expected distortion under uneven error protection.
  • To develop a computationally efficient algorithm for solving the generalized RDOP problem.
  • To analyze the performance of the proposed algorithm for image transmission.

Main Methods:

  • Formulation of the generalized RDOP problem for embedded bitstreams.
  • Extension of dynamic programming (DP) algorithms to solve the problem.
  • Development of a novel divide-and-conquer (D&C) algorithm leveraging matrix search in totally monotone matrices.
  • Experimental evaluation using SPIHT coded images.

Main Results:

  • The proposed D&C algorithm achieves a global optimal solution for RDOP with convex rate-distortion (R-D) curves.
  • The D&C algorithm reduces computational complexity from O(K^2LN) to O(NKL log K) compared to DP.
  • Experiments demonstrate significant speedup in practice for image transmission.

Conclusions:

  • The novel D&C algorithm provides a significant speedup for rate-distortion optimal packetization.
  • This advancement is crucial for efficient and robust image transmission over noisy packet networks.
  • The method effectively minimizes distortion and handles complex error protection scenarios.