Paper
25 October 2013 Disparity map estimation using image pyramid
Mikołaj Roszkowski
Author Affiliations +
Proceedings Volume 8903, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013; 89030I (2013) https://doi.org/10.1117/12.2035281
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013, 2013, Wilga, Poland
Abstract
The task of a short baseline stereo matching algorithm is to calculate the disparity map given two rectified images of one scene. Most algorithms assume that a maximal possible disparity exists and search all disparities in the range from 1 to this maximal disparity. In the case of large images and wide disparity search range this can be very computationally demanding. In this article a simple coarse to fine hierarchical matching method based on the Gaussian pyramid and local stereo matching is investigated. Such an approach allows significant reduction of the number of disparities searched compared to the full search algorithm. Moreover it is shown, that grouping pixels into simple square regions is in most cases sufficient to avoid significant errors that typically appear at disparity map discontinuities when hierarchical schemes are used. Finally, it is presented that in most cases the quality of the disparity map obtained using the investigated algorithm is of comparable quality to a disparity map obtained using full-search local stereo algorithm.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mikołaj Roszkowski "Disparity map estimation using image pyramid", Proc. SPIE 8903, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013, 89030I (25 October 2013); https://doi.org/10.1117/12.2035281
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Cited by 2 scholarly publications.
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KEYWORDS
Venus

Image filtering

Image analysis

Image resolution

Field programmable gate arrays

Image processing algorithms and systems

Image segmentation

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