2,441 research outputs found
A Framework for SAR-Optical Stereogrammetry over Urban Areas
Currently, numerous remote sensing satellites provide a huge volume of
diverse earth observation data. As these data show different features regarding
resolution, accuracy, coverage, and spectral imaging ability, fusion techniques
are required to integrate the different properties of each sensor and produce
useful information. For example, synthetic aperture radar (SAR) data can be
fused with optical imagery to produce 3D information using stereogrammetric
methods. The main focus of this study is to investigate the possibility of
applying a stereogrammetry pipeline to very-high-resolution (VHR) SAR-optical
image pairs. For this purpose, the applicability of semi-global matching is
investigated in this unconventional multi-sensor setting. To support the image
matching by reducing the search space and accelerating the identification of
correct, reliable matches, the possibility of establishing an epipolarity
constraint for VHR SAR-optical image pairs is investigated as well. In
addition, it is shown that the absolute geolocation accuracy of VHR optical
imagery with respect to VHR SAR imagery such as provided by TerraSAR-X can be
improved by a multi-sensor block adjustment formulation based on rational
polynomial coefficients. Finally, the feasibility of generating point clouds
with a median accuracy of about 2m is demonstrated and confirms the potential
of 3D reconstruction from SAR-optical image pairs over urban areas.Comment: This is the pre-acceptance version, to read the final version, please
go to ISPRS Journal of Photogrammetry and Remote Sensing on ScienceDirec
An Epipolar Line from a Single Pixel
Computing the epipolar geometry from feature points between cameras with very
different viewpoints is often error prone, as an object's appearance can vary
greatly between images. For such cases, it has been shown that using motion
extracted from video can achieve much better results than using a static image.
This paper extends these earlier works based on the scene dynamics. In this
paper we propose a new method to compute the epipolar geometry from a video
stream, by exploiting the following observation: For a pixel p in Image A, all
pixels corresponding to p in Image B are on the same epipolar line.
Equivalently, the image of the line going through camera A's center and p is an
epipolar line in B. Therefore, when cameras A and B are synchronized, the
momentary images of two objects projecting to the same pixel, p, in camera A at
times t1 and t2, lie on an epipolar line in camera B. Based on this observation
we achieve fast and precise computation of epipolar lines. Calibrating cameras
based on our method of finding epipolar lines is much faster and more robust
than previous methods.Comment: WACV 201
Wide baseline stereo matching with convex bounded-distortion constraints
Finding correspondences in wide baseline setups is a challenging problem.
Existing approaches have focused largely on developing better feature
descriptors for correspondence and on accurate recovery of epipolar line
constraints. This paper focuses on the challenging problem of finding
correspondences once approximate epipolar constraints are given. We introduce a
novel method that integrates a deformation model. Specifically, we formulate
the problem as finding the largest number of corresponding points related by a
bounded distortion map that obeys the given epipolar constraints. We show that,
while the set of bounded distortion maps is not convex, the subset of maps that
obey the epipolar line constraints is convex, allowing us to introduce an
efficient algorithm for matching. We further utilize a robust cost function for
matching and employ majorization-minimization for its optimization. Our
experiments indicate that our method finds significantly more accurate maps
than existing approaches
Towards Automatic SAR-Optical Stereogrammetry over Urban Areas using Very High Resolution Imagery
In this paper we discuss the potential and challenges regarding SAR-optical
stereogrammetry for urban areas, using very-high-resolution (VHR) remote
sensing imagery. Since we do this mainly from a geometrical point of view, we
first analyze the height reconstruction accuracy to be expected for different
stereogrammetric configurations. Then, we propose a strategy for simultaneous
tie point matching and 3D reconstruction, which exploits an epipolar-like
search window constraint. To drive the matching and ensure some robustness, we
combine different established handcrafted similarity measures. For the
experiments, we use real test data acquired by the Worldview-2, TerraSAR-X and
MEMPHIS sensors. Our results show that SAR-optical stereogrammetry using VHR
imagery is generally feasible with 3D positioning accuracies in the
meter-domain, although the matching of these strongly hetereogeneous
multi-sensor data remains very challenging. Keywords: Synthetic Aperture Radar
(SAR), optical images, remote sensing, data fusion, stereogrammetr
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