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

Search research articles

Related Experiment Videos

Fixed bit-rate image compression using a parallel-structure multilayer neural network.

Y Benbenisti¹, D Kornreich, H B Mitchell

¹Department of Computer Science and Electrical Engineering, Ben-Gurion University of the Negev, Be'er Sheva, Israel.

IEEE Transactions on Neural Networks

|February 7, 2008

Summary

This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by

Same author

Colchicine: an ancient drug with novel applications.

The British journal of dermatology·2017

Same author

Dysfunctional immune-privilege in morbid obesity: implications and effect of gastric bypass surgery.

Obesity surgery·2003

Same author

Effect of surgically-induced weight loss on leukocyte indicators of chronic inflammation in morbid obesity.

Obesity surgery·2002

Same author

The effect of obesity on neutrophil Fc receptors and adhesion molecules (CD16, CD11b, CD62L).

Obesity surgery·2002

Same author

Prostaglandin E2 receptors EP2 and EP4 are down-regulated in human mononuclear cells after injury.

Surgery·2001

Same author

NS-398 treatment after trauma modifies NF-kappaB activation and improves survival.

The Journal of surgical research·2001

Same journal

Universal perceptron and DNA-like learning algorithm for binary neural networks: LSBF and PBF implementations.

IEEE transactions on neural networks·2013

Same journal

Guest editorial: special section on white box nonlinear prediction models.

IEEE transactions on neural networks·2011

Same journal

Data-based fault-tolerant control of high-speed trains with traction/braking notch nonlinearities and actuator failures.

IEEE transactions on neural networks·2011

Same journal

Guest editorial: special section on data-based control, modeling, and optimization.

IEEE transactions on neural networks·2011

Same journal

Neural network-based multiple robot simultaneous localization and mapping.

IEEE transactions on neural networks·2011

Same journal

Data-driven model-free adaptive control for a class of MIMO nonlinear discrete-time systems.

IEEE transactions on neural networks·2011

See all related articles

This study introduces a novel parallel neural network structure for picture compression, significantly improving efficiency and quality. The new method offers low complexity, high picture quality, and a fixed bit-rate, overcoming limitations of existing algorithms.

Area of Science:

Computer Vision
Machine Learning
Image Processing

Background:

Recent advancements in picture compression utilize parallel neural network structures.
Existing algorithms, while robust, present challenges like high computational complexity, moderate image quality, and variable bit-rates.

Purpose of the Study:

To develop a novel parallel structure for picture compression that addresses the drawbacks of current methods.
To achieve low computational complexity, high reconstructed picture quality, and a fixed bit-rate.

Main Methods:

Implementation of a simple parallel structure utilizing neural networks.
Focus on optimizing for computational efficiency and image fidelity.

Main Results:

Related Experiment Videos

The proposed structure demonstrates low computational complexity.

High quality of decompressed pictures is achieved.

A fixed bit-rate is successfully maintained.

Conclusions:

The developed simple parallel structure effectively eliminates the drawbacks of previous neural network-based picture compression algorithms.
This approach offers a superior solution for efficient and high-quality image compression.