Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Downsampling

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...

Upsampling

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...

Uniform Depth Channel Flow: Problem Solving

Uniform Depth Channel Flow: Problem Solving

To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...

Uniform Depth Channel Flow

Uniform Depth Channel Flow

Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...

Reducing Line Loss

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...

Deconvolution

Deconvolution

Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026

Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026

Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026

Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026

Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026

Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026

Search research articles

Related Experiment Video

Updated: Jun 9, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Information Bottleneck Driven Deep Video Compression-IBOpenDVCW.

Timor Leiderman¹, Yosef Ben Ezra¹

¹Faculty of Electrical Engineering, Holon Institute of Technology, 52 Golomb Str., P.O. Box 305, Holon 58102, Israel.

Entropy (Basel, Switzerland)

|October 25, 2024

Summary

This summary is machine-generated.

This study introduces a novel video compression method combining information bottleneck theory and wavelet transforms. The new approach enhances rate-distortion performance, outperforming current state-of-the-art techniques.

Keywords:

deep video compression information bottleneck neural networks wavelets

More Related Videos

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain In Vivo Calcium Imaging

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain In Vivo Calcium Imaging

Published on: October 8, 2021

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

Related Experiment Videos

Last Updated: Jun 9, 2025

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain In Vivo Calcium Imaging

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain In Vivo Calcium Imaging

Published on: October 8, 2021

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Profiling Maternal Behavior Responses During Whole-Brain Imaging

Published on: January 24, 2025

Area of Science:

Computer Science
Signal Processing
Information Theory

Background:

Deep learning models have advanced video coding, but compression remains challenging.
Information Bottleneck (IB) theory offers a framework for understanding optimal information compression.

Purpose of the Study:

To develop a novel video compression approach integrating IB theory and wavelet transforms.
To analyze the impact of wavelet properties and advanced pooling on information compression.

Main Methods:

Implemented a novel video compression model inspired by Information Bottleneck (IB) theory.
Integrated discrete wavelet transform (DWT) as an advanced pooling method, replacing average pooling.
Analyzed information and mutual information across different mother wavelets and decomposition levels.

Main Results:

The proposed IB-theory-based wavelet video compression model demonstrated superior performance.
The DWT-based pooling method positively impacted information compression metrics.
Achieved competitive rate-distortion performance against established codecs like AVC/H.264 and HEVC/H.265.

Conclusions:

Combining IB theory with wavelet transforms offers a promising direction for advanced video compression.
The proposed method achieves state-of-the-art results, advancing the field of video coding.