DocumentCode :
1494071
Title :
Precise Subpixel Disparity Measurement From Very Narrow Baseline Stereo
Author :
Morgan, Gareth Llewellyn Keith ; Liu, Jian Guo ; Yan, Hongshi
Author_Institution :
Dept. of Earth Sci. & Eng., Imperial Coll. London, London, UK
Volume :
48
Issue :
9
fYear :
2010
Firstpage :
3424
Lastpage :
3433
Abstract :
To obtain depth-from-stereo imagery, it is traditionally required that the baseline separation between images (or the base-to-height ratio) be very large in order to ensure the largest image disparity range for effective measurement. Typically, a B/H ratio in the range of 0.6-1 is preferred. As a consequence, most existing stereo-matching algorithms are designed to measure disparities reliably with only integer-pixel precision. However, wide baselines may increase the possibility of occlusion occurring between highly contrasting relief, imposing a serious problem to digital elevation model (DEM) generation in urban and highly dissected mountainous areas. A narrow-baseline stereo configuration can alleviate the problem significantly but requires very precise measurements of disparity at subpixel levels. In this paper, we demonstrate a stereo-matching algorithm, based upon the robust phase correlation method, that is capable of directly measuring disparities up to 1/50th pixel accuracy and precision. The algorithm enables complete and dense surface shape information to be retrieved from images with unconventionally low B/H ratios (e.g., less than 0.01), potentially allowing DEM generation from images that would otherwise not be deemed suitable for the purpose.
Keywords :
digital elevation models; geophysical image processing; geophysical techniques; stereo image processing; base-to-height ratio; digital elevation model; image disparity range; integer-pixel precision; narrow-baseline stereo configuration; precise subpixel disparity measurement; robust phase correlation method; stereo imagery; stereo-matching algorithms; Algorithm design and analysis; Cameras; Digital elevation models; Geometry; Pixel; Robustness; Satellites; Shape measurement; Stereo vision; Surface topography; Digital elevation model (DEM); phase correlation (PC); stereo vision; subpixel;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2010.2046672
Filename :
5466239
Link To Document :
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