In the field of compressed sensing, l1-2$\ell _{1-2}$-minimization model can recover the sparse signal well. In dealing with the l1-2$\ell _{1-2}$-minimization problem, most of the existing literature uses the differe...
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In the field of compressed sensing, l1-2$\ell _{1-2}$-minimization model can recover the sparse signal well. In dealing with the l1-2$\ell _{1-2}$-minimization problem, most of the existing literature uses the difference of convex algorithm (DCA) to solve the unrestricted l1-2$\ell _{1-2}$-minimization model, that is, model (4). Although experiments have proved that the unrestricted l1-2$\ell _{1-2}$-minimization model can recover the original sparse signal, the theoretical proof has not been established yet. This paper mainly proves theoretically that the unrestricted l1-2$\ell _{1-2}$-minimization model can recover the sparse signal well, and makes an experimental study on the parameter lambda in the unrestricted minimization model. The experimental results show that increasing the size of parameter lambda in (4) appropriately can improve the recovery success rate. However, when lambda is sufficiently large, increasing lambda will not increase the recovery success rate.
This paper mainly studies the method of water meter plum pin precise positioning, and proposes a positioning method of water meter plum blossom needle with high positioning accuracy, anti-jamming performance and versa...
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ISBN:
(纸本)9781538684818
This paper mainly studies the method of water meter plum pin precise positioning, and proposes a positioning method of water meter plum blossom needle with high positioning accuracy, anti-jamming performance and versatility. The method firstly uses the three-frame difference method to obtain the contour area of the plum blossom needle dynamically, secondly the convex hull algorithm to extract the boundary information of the plum blossom needle, and then uses the minimum encircling circle algorithm to create the circumscribed circle of the plum blossom needle. By traversing the distance between each vertex and the circumcircle pixel, we find the exact coordinate position and achieve the precise positioning of the plum blossom needle. The test results show that the precision of the water meter can reach 97.46%-99.133% by accurately positioning the plum blossom needle. On the one hand we can accurately locate the plum blossom needle with the bubble inside the dial, on the other hand, this method covers the shortage of the traditional photoelectric pulse verification method which can only detect the water meter of the plum blossom needle at the same position.
We develop a tractable algorithms for finding the optimal power spectral density of the Gaussian input excitation for identifying a Wiener model. This problem is known as a difficult problem for two reasons. Firstly, ...
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In general, image reconstruction from metal-embedded data causes streak artifacts that reduce the quality of the reconstructed image. In this paper, the attempt has been conducted to solve the problem of metal artifac...
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ISBN:
(纸本)9781424421015
In general, image reconstruction from metal-embedded data causes streak artifacts that reduce the quality of the reconstructed image. In this paper, the attempt has been conducted to solve the problem of metal artifacts in cone-beam X-ray CT. The proposed method is applied directly to CT measurement data. First. the metal objects in the reconstructed image are detected and then reprojected to obtain the raw data using cone-beam reconstruction. The missing projections caused by the metal objects are replaced with their surrounding unaffected area through interpolation. Finally, the corrected raw data are reconstructed with the convex algorithm, which is the iterative algorithm for maximizing the likelihood function. The reconstructed images of metal artifact data using statistical reconstruction tends to be superior to conventional filtered backprojection (FBP) reconstruction.
We analyse the performance of statistical reconstruction (SR) methods when applied to non-continuous x-ray detectors. Robustness to projection gaps is required in x-ray CT systems with multiple detector modules or wit...
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We analyse the performance of statistical reconstruction (SR) methods when applied to non-continuous x-ray detectors. Robustness to projection gaps is required in x-ray CT systems with multiple detector modules or with defective detector pixels. In such situations, the advantage of statistical reconstruction is that it is able to ignore missing or faulty pixels and that it makes optimal use of the remaining line integrals. This potentially obviates the need to fill the sinogram discontinuities by interpolation or any other approximative preprocessing techniques. In this paper, we apply SR to cone beam projections of (i) a hypothetical modular detector micro-CT scanner and of (ii) a system with randomly located defective detector elements. For the modular-detector system, SR produces reconstruction volumes free of noticeable gap-induced artefacts as long as the location of detector gaps and selection of the scanning range provide complete object sampling in the central imaging plane. When applied to randomly located faulty detector elements, SR produces images free of substantial ring artefacts even for cases where defective pixels cover as much as 3% of the detector area.
X-ray CT images obtained with iterative reconstruction (IR) can be hampered by the so-called edge and aliasing artefacts, which appear as interference patterns and severe overshoots in the areas of sharp intensity tra...
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X-ray CT images obtained with iterative reconstruction (IR) can be hampered by the so-called edge and aliasing artefacts, which appear as interference patterns and severe overshoots in the areas of sharp intensity transitions. Previously, we have demonstrated that these artefacts are caused by discretization errors during the projection simulation step in IR. Although these errors are inherent to IR, they can be adequately suppressed by reconstruction on an image grid that is finer than that typically used for analytical methods such as filtered back-projection. Two other methods that may prevent edge artefacts are: (i) smoothing the projections prior to reconstruction or (ii) using an image representation different from voxels;spherically symmetric Kaiser-Bessel functions are a frequently employed example of such a representation. In this paper, we compare reconstruction on a fine grid with the two above-mentioned alternative strategies for edge artefact reduction. We show that the use of a fine grid results in a more adequate suppression of artefacts than the smoothing of projections or using the Kaiser-Bessel image representation.
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