&lt;title&gt;Projection registration in reflective tomography&lt;/title&gt;

Ford, Stephen D.; Matson, Charles L.

doi:10.1117/12.364128

Cited by 7 publications

(3 citation statements)

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“…Fig.7 contains the corresponding transformed transmissive projections from reflective projections. Fig.6 The range-resolved reflective intensity data of the target as a function of range and projection angle The projections need to be filtered with the |k| filter to boost the high spatial frequencies and avoid artifacts [10]. Then we can get the Fourier domain based on the Fourier-Slice theorem.…”

Section: Computer Simulation Resultsmentioning

confidence: 99%

Modified radon-Fourier transform for reflective tomography laser radar imaging

et al. 2011

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This paper presents imaging result of computer simulation using a modified Radon-Fourier transform algorithm to reconstruct images from reflective tomography data. Since the signal returned is reflected off the illuminated outer surface of an opaque target, only information about the exterior of the target can be obtained, and the images reconstructed using reflective tomography techniques is an outline view of the target cross section. The projection ( , ) p r φ and ( , )p r φ + o contain different information about the target surface, and will lead different Fourier estimates along the same line through the origin based on the standard Fourier-Slice tomography theorem. Here, using the functional similarity between transmission tomography and reflective tomography, we add the collinear reflective projections to become corresponding transmissive projections before Fourier transform. Then the target can be reconstructed from the Fourier domain using the same operations in transmission tomography. The computer simulation result demonstrates the effectiveness of this modified algorithm to reconstruct image in reflective tomography using the diffuse reflection model (lamberts body). Future research will include the development of image reconstruction based on this modified algorithm for targets with much more complicated reflective characters.

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Section: Computer Simulation Resultsmentioning

confidence: 99%

Modified radon-Fourier transform for reflective tomography laser radar imaging

et al. 2011

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“…Firstly, a brief of filtered back-projection [8,9], a standard method of tomography, is provided for reflective variable, c % is the filter function, which is the product of a window function and the magnitude of the spatial frequency [2,10,12,14] |…”

Section: Review Of Filtered Back-projectionmentioning

confidence: 99%

“…The range-resolved Laser radar reflective tomography imaging laser radar was firstly introduced by researchers Parker [1,2], Knight [3,4] at the Massachusetts Institute of Technology. Several years later, Matson [5][6][7][8][9][10][11] in Air Force began exploring the technique of using the HI-CLASS coherent laser radar system to obtain reflective images by carrying out a heterodyne system analysis, deriving and validating imaging signal to noise ratio expressions and so on.…”

Section: Introductionmentioning

confidence: 99%

Filters effects for different objects surfaces in reflective tomography laser radar

Jin

Sun

Yan

et al. 2010

Detectors and Imaging Devices: Infrared, Focal Plane, Single Photon

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In range-resolved reflective tomography laser radar imaging system, different objects surfaces have a major impact on signals reflected, and the corresponding different filters in filtered back-projection algorithm would attenuate varying degree artifacts in the resulting images reconstructed. In this paper, light reflection from a surface is described by the Stanford-Robertson bidirectional reflectance distribution function (SR BRDF) model developed by the Air Force.Different reflective parameters in SR BRDF were assumed to simulate various surfaces with different proportion between diffuse reflection and specular reflection. The projections of objects were simulated with 1 degree view increment covering the entire angular domain. We also add the experimental imaging results to validate the effectiveness of this SR BRDF model in reflection tomography. Several filters with different parameters were applied and the quality of images reconstruction was compared, especially beam hardening artifacts and the crossed streak artifacts.

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