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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

Foveated video compression with optimal rate control.

S Lee¹, M S Pattichis, A C Bovik

¹Bell Laboratories, Lucent Technologies, Murray Hill, NJ 07974, USA.

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

|February 6, 2008

Summary

This summary is machine-generated.

This study introduces a foveated video compression framework using nonuniform filtering to enhance video compressibility. The new method maximizes foveal signal-to-noise ratio (FSNR) for superior visual quality at reduced bit rates.

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 Vision
Digital Signal Processing
Video Compression

Background:

Human visual system exhibits nonuniform sampling, with higher acuity in the fovea.
Existing foveated video compression aims to leverage this nonuniformity for efficiency.
Nonuniform filtering can increase video stream compressibility.

Purpose of the Study:

To develop a foveated video compression framework using nonuniform filtering.
To maximize the foveal signal-to-noise ratio (FSNR) for optimal visual quality.
To establish new rate control algorithms for efficient video compression.

Main Methods:

Implemented a nonuniform filtering scheme for foveated video creation.
Developed an optimal rate control algorithm maximizing FSNR using Lagrange multipliers.
Introduced a piecewise rate-distortion/rate-quantization (R-D/R-Q) model.
Presented a fast algorithm for optimal Lagrange multiplier search.
Developed a suboptimal rate control algorithm for H.263/MPEG video coding.

Main Results:

Demonstrated improved reconstructed video quality with maximized FSNR.
Showcased coding performance for H.263+/MPEG-4 video coding.
Foveated video coding with the suboptimal algorithm achieved excellent performance below 64 kb/s.
Compared reconstructed pictures from optimal rate control for foveated and normal video.

Conclusions:

The proposed foveated video compression framework effectively enhances compressibility.
The novel FSNR metric and rate control algorithms optimize visual quality for target bit rates.
The suboptimal rate control algorithm offers high performance for real-time applications.