Ghost imaging is a transverse imaging technique that allows an object to be reconstructed using the correlation between a pair of light fields. As known, in ghost imaging configurations, a large number of realizations are usually required for reconstruction of the objects. To reduce the number of realizations, Chen et al. [Opt. Lett.38, 546-548 (2013)OPLEDP0146-959210.1364/OL.38.000546] demonstrated an object authentication method with computational ghost imaging using realizations of less than 5% of the Nyquist limit. In this paper, we have further improved this method using a "compressive sensing algorithm" instead of a "classical correlation algorithm in computational ghost imaging." As a result, the realizations for object authentication were further reduced from 5% of the Nyquist limit to 3% of the Nyquist limit.
This paper presents a novel image matching method for multi-source satellite images, which integrates global Shuttle Radar Topography Mission (SRTM) data and image segmentation to achieve robust and numerous correspondences. This method first generates the epipolar lines as a geometric constraint assisted by global SRTM data, after which the seed points are selected and matched. To produce more reliable matching results, a region segmentation-based matching propagation is proposed in this paper, whereby the region segmentations are extracted by image segmentation and are considered to be a spatial constraint. Moreover, a similarity measure integrating Distance, Angle and Normalized Cross-Correlation (DANCC), which considers geometric similarity and radiometric similarity, is introduced to find the optimal correspondences. Experiments using typical satellite images acquired from Resources Satellite-3 (ZY-3), Mapping Satellite-1, SPOT-5 and Google Earth demonstrated that the proposed method is able to produce reliable and accurate matching results.
A central catadioptric-perspective camera system is widely used nowadays. A critical problem is that current calibration methods cannot determine the extrinsic parameters between the central catadioptric camera and a perspective camera effectively. We present a novel calibration method for a central catadioptric-perspective camera system, in which the central catadioptric camera has a hyperbolic mirror. Two cameras are used to capture images of one calibration pattern at different spatial positions. A virtual camera is constructed at the origin of the central catadioptric camera and faced toward the calibration pattern. The transformation between the virtual camera and the calibration pattern could be computed first and the extrinsic parameters between the central catadioptric camera and the calibration pattern could be obtained. Three-dimensional reconstruction results of the calibration pattern show a high accuracy and validate the feasibility of our method.
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