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Extraction: Partition and Distribution Coefficients01:14

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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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A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
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Related Experiment Video

Updated: Mar 18, 2026

Characterization of Anisotropic Leaky Mode Modulators for Holovideo
09:36

Characterization of Anisotropic Leaky Mode Modulators for Holovideo

Published on: March 19, 2016

8.4K

Fast entropy-based CABAC rate estimation for mode decision in HEVC.

Wei-Gang Chen1, Xun Wang1

  • 1School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, 310018 China.

Springerplus
|July 8, 2016
PubMed
Summary

This study introduces a faster entropy-based rate estimator for High Efficiency Video Coding (HEVC) Context Adaptive Binary Arithmetic Coding (CABAC). The new method significantly reduces computational complexity in mode decision with minimal impact on video quality.

Keywords:
Context-adaptive binary arithmetic codingHigh efficiency video codingMode decisionRate estimationRate-distortion optimization

Related Experiment Videos

Last Updated: Mar 18, 2026

Characterization of Anisotropic Leaky Mode Modulators for Holovideo
09:36

Characterization of Anisotropic Leaky Mode Modulators for Holovideo

Published on: March 19, 2016

8.4K

Area of Science:

  • Video compression algorithms
  • Digital signal processing
  • Information theory

Background:

  • High Efficiency Video Coding (HEVC) utilizes Context Adaptive Binary Arithmetic Coding (CABAC) for entropy coding.
  • CABAC's sequential nature and data dependencies create computational bottlenecks in HEVC mode decision.
  • Existing fast rate estimation methods for CABAC incompletely address complexity reduction.

Purpose of the Study:

  • To develop a novel, fast entropy-based CABAC rate estimator for HEVC.
  • To significantly reduce the computational complexity of the mode decision process in HEVC encoders.
  • To maintain negligible loss in video quality (PSNR) and coding efficiency (BD-rate).

Main Methods:

  • Proposing a fast entropy-based CABAC rate estimator that bypasses binarization, context modeling, and arithmetic coding steps.
  • Evaluating the proposed estimator's performance against typical approaches in HEVC mode decision.
  • Measuring computational complexity reduction, Peak Signal-to-Noise Ratio (PSNR) loss, and Bjontegaard Delta (BD)-rate increment.

Main Results:

  • The proposed fast CABAC rate estimator reduces HEVC mode decision computational complexity by 9-23%.
  • Negligible Peak Signal-to-Noise Ratio (PSNR) loss was observed with the proposed method.
  • Minimal Bjontegaard Delta (BD)-rate increment indicates maintained coding efficiency.

Conclusions:

  • The developed fast entropy-based CABAC rate estimator offers significant computational savings for HEVC.
  • The estimator is practical for implementation in real-world HEVC encoders without compromising video quality.
  • This advancement contributes to more efficient video compression and encoding processes.