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Related Experiment Video

Updated: Jul 7, 2026

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

2D-pattern matching image and video compression: theory, algorithms, and experiments.

Marc Alzina¹, Wojciech Szpankowski, Ananth Grama

¹ENST, Paris, France. alzina@email.enst.fr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 5, 2008

Summary

This summary is machine-generated.

This study introduces a lossy data compression framework using approximate 2D pattern matching, extending Lempel-Ziv lossless methods for efficient image and video compression with fast decompression.

Related Experiment Videos

Last Updated: Jul 7, 2026

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

Area of Science:

Computer Science
Information Theory
Digital Signal Processing

Background:

Lossless data compression algorithms like Lempel-Ziv are foundational but can be extended for lossy applications.
Existing lossy schemes often involve complex techniques like prediction or interpolation.
Efficient compression for multimedia applications requires balancing compression ratio, speed, and quality.

Purpose of the Study:

To propose a novel lossy data compression framework based on approximate 2D pattern matching (2D-PMC).
To adapt the Lempel-Ziv lossless scheme for lossy compression of images and videos.
To investigate the theoretical and experimental performance of the proposed framework.

Main Methods:

Extension of the Lempel-Ziv scheme using approximate 2D pattern matching.
Application of fixed and growing database models for video and image compression, respectively.
Implementation utilizing k-d trees, generalized run length coding, adaptive arithmetic coding, and adaptive distortion levels.

Main Results:

Demonstrated bit rates of 0.25-0.5 bpp for high-quality images and 0.15-0.5 Mbps for video.
Achieved good compression ratios at high compression speeds.
Showcased extremely fast decompression capabilities, suitable for networked multimedia.

Conclusions:

The proposed 2D-PMC framework offers an effective approach to lossy data compression.
The framework provides a basis for integrating various advanced compression techniques.
The scheme's efficiency and fast decompression make it ideal for real-time multimedia applications.