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Related Experiment Video

Updated: Jun 4, 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

Depth no-synthesis-error model for view synthesis in 3-D video.

Yin Zhao¹, Ce Zhu, Zhenzhong Chen

¹School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang, Singapore. zhaoyin@zju.edu.cn

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

|February 24, 2011

Summary

A new Depth No-Synthesis-Error (D-NOSE) model allows virtual 3-D video views to be synthesized losslessly. This model defines acceptable depth distortions, preventing geometry changes and preserving occlusion order for improved depth coding.

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Area of Science:

Computer Vision
Image Processing
3-D Video Technology

Background:

Stereoscopic 3-D video relies on Depth Image-Based Rendering (DIBR) for virtual view synthesis.
Depth map distortions in DIBR can cause unwanted geometry changes and occlusion variations.
Limited disparity levels in 8-bit depth data mean some distortions may not affect synthesized views.

Purpose of the Study:

To develop a model for determining allowable depth distortions in DIBR.
To ensure virtual view synthesis without geometry changes or occlusion order compromise.
To enable lossless virtual view synthesis and enhance depth coding efficiency.

Main Methods:

Developed the Depth No-Synthesis-Error (D-NOSE) model.
Analyzed allowable depth distortions for rendering virtual views without geometric alterations.
Investigated the impact of D-NOSE on occlusion order preservation during view synthesis.

Main Results:

The D-NOSE model precisely defines thresholds for depth distortions that do not introduce geometry changes.
Depth distortions within D-NOSE limits maintain the correct occlusion order in synthesized views.
Simulations confirmed lossless virtual view synthesis and demonstrated gains in depth coding using the D-NOSE model.

Conclusions:

The D-NOSE model provides a robust method for lossless virtual view synthesis in 3-D video.
Adherence to D-NOSE thresholds guarantees the integrity of geometry and occlusion in synthesized views.
The D-NOSE model offers significant advantages for depth map coding and 3-D video processing.