&lt;title&gt;Application of fast back-projection techniques for some inverse problems of synthetic aperture radar&lt;/title&gt;

Nilsson, S.; Andersson, Lars

doi:10.1117/12.321872

Cited by 23 publications

(23 citation statements)

References 3 publications

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“…Recently, algorithms have been suggested which provide a speed-up of the filtered back-projection algorithm for SAR inversion. They operate in the time domain and include two-stage [13][14][15] and multiple-stage back-projection [16][17][18]. These algorithms exploit the fundamental redundancy between nearby aperture positions for high-frequency reflectivity components in the along-track direction.…”

Section: Introductionmentioning

confidence: 99%

Synthetic-aperture radar processing using fast factorized back-projection

Ulander

Hellsten

Stenström

2003

IEEE Trans. Aerosp. Electron. Syst.

684

409

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Exact synthetic aperture radar (SAR) inversion for a linear aperture may be obtained using fast transform techniques. Alternatively, back-projection integration in time domain can also be used. This technique has the benefit of handling a general aperture geometry. In the past, however, back-projection has seldom been used due to heavy computational burden. We show that the back-projection integral can be recursively partitioned and an effective algorithm constructed based on aperture factorization. By representing images in local polar coordinates it is shown that the number of operations is drastically reduced and can be made to approach that of fast transform algorithms. The algorithm is applied to data from the airborne ultra-wideband CARABAS SAR and shown to give a reduction in processing time of two to three orders of magnitude.

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Section: Introductionmentioning

confidence: 99%

Synthetic-aperture radar processing using fast factorized back-projection

Ulander

Hellsten

Stenström

2003

IEEE Trans. Aerosp. Electron. Syst.

684

409

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show abstract

“…For some of the most important simple geometrical shapes of closed manifolds Γ, there exist analytical reconstruction formulae of series expansion and/or filtered backprojection type (see again [24] and the references therein, for instance [33,34,13,43,32,38,15,14,10]). This paper focuses on the case where Γ is a sphere in R 2 (circle) or R 3 .…”

Section: Photoacoustic Imaging As An Inverse Problemmentioning

confidence: 99%

Texture Generation for Photoacoustic Elastography

2015

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Elastographic imaging is a widely used technique which can in principle be implemented on top of every imaging modality. In elastography, the specimen is exposed to a force causing local displacements in the probe, and imaging is performed before and during the displacement experiment. From the computed displacements material parameters can be deduced, which in turn can be used for clinical diagnosis. Photoacoustic imaging is an emerging image modality, which exhibits functional and morphological contrast. However, opposed to ultrasound imaging, for instance, it is considered a modality which is not suited for elastography, because it does not reveal speckle patterns. However, this is somehow counter-intuitive, because photoacoustic imaging makes available the whole frequency spectrum as opposed to single frequency standard ultrasound imaging. In this work, we show that in fact artificial speckle patterns can be introduced by using only a band-limited part of the measurement data. We also show that after introduction of artificial speckle patterns, deformation estimation can be implemented more reliably in photoacoustic imaging.

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“…with Q = 3Q(Rc Q,R ) e Rc Q,R . Equation (27) provides the smoothness estimate necessary to invoke Corollary 3. It is applied first in the y 1 variable, then in the y 2 variable.…”

Section: Recursive Dyadic Interpolationmentioning

confidence: 99%