Paper
24 May 1999 Error-tolerant interpolation of intermediate views for real-time applications
Matthias Lueck, Hartmut Schroeder
Author Affiliations +
Proceedings Volume 3639, Stereoscopic Displays and Virtual Reality Systems VI; (1999) https://doi.org/10.1117/12.349382
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
Many applications in 3D imaging demand for the calculation of intermediate views. In this paper a system is proposed which consists of a predictive disparity estimation module and an interpolation module based on non-linear filter techniques. The predictive disparity estimation algorithm is of low computational costs and gives smooth and dense estimation results. Problems of block-based estimation algorithms in general are the edges of objects because occlusion occurs in this region and the disparity maps are inaccurate. A postprocessing algorithm of low complexity avoids blocking artifacts, that are very annoying in the regions of disparity discontinuities. The interpolation is based on rank order filters called weighted median filters. By an appropriate choice of the weighted median filter root structures main picture elements are also interpolated correctly if faulty disparity vectors occur. With this technique it is possible to avoid interpolation artifacts, resulting from inaccuracies of disparity maps estimated by block based algorithms. In this paper the development of weighted median filters for median applications and the adaptation of the filters to the synthesized viewpoint are presented.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthias Lueck and Hartmut Schroeder "Error-tolerant interpolation of intermediate views for real-time applications", Proc. SPIE 3639, Stereoscopic Displays and Virtual Reality Systems VI, (24 May 1999); https://doi.org/10.1117/12.349382
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KEYWORDS
Digital filtering

Cameras

Nonlinear filtering

Filtering (signal processing)

Image filtering

Error analysis

Optimal filtering

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