05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access A GPU-accelerated light-field super-resolution framework based on mixed noise model and weighted regularization(2022) Tran, Trung-Hieu; Sun, Kaicong; Simon, SvenLight-field (LF) super-resolution (SR) plays an essential role in alleviating the current technology challenge in the acquisition of a 4D LF, which assembles both high-density angular and spatial information. Due to the algorithm complexity and data-intensive property of LF images, LFSR demands a significant computational effort and results in a long CPU processing time. This paper presents a GPU-accelerated computational framework for reconstructing high-resolution (HR) LF images under a mixed Gaussian-Impulse noise condition. The main focus is on developing a high-performance approach considering processing speed and reconstruction quality. From a statistical perspective, we derive a joint ℓ1- ℓ2data fidelity term for penalizing the HR reconstruction error taking into account the mixed noise situation. For regularization, we employ the weighted non-local total variation approach, which allows us to effectively realize LF image prior through a proper weighting scheme. We show that the alternating direction method of the multipliers algorithm (ADMM) can be used to simplify the computation complexity and results in a high-performance parallel computation on the GPU Platform. An extensive experiment is conducted on both synthetic 4D LF dataset and natural image dataset to validate the proposed SR model’s robustness and evaluate the accelerated optimizer’s performance. The experimental results show that our approach achieves better reconstruction quality under severe mixed-noise conditions as compared to the state-of-the-art approaches. In addition, the proposed approach overcomes the limitation of the previous work in handling large-scale SR tasks. While fitting within a single off-the-shelf GPU, the proposed accelerator provides an average speedup of 2.46 ×and 1.57 ×for ×2and ×3SR tasks, respectively. In addition, a speedup of 77×is achieved as compared to CPU execution.Item Open Access Steered fiber orientation : correlating orientation and residual tensile strength parameters of SFRC(2022) Medeghini, Filippo; Guhathakurta, Jajnabalkya; Tiberti, Giuseppe; Simon, Sven; Plizzari, Giovanni A.; Mark, PeterAdding steel fibers to concrete improves the post-cracking tensile strength of the composite material due to fibers bridging the cracks. The residual performance of the material is influenced by fiber type, content and orientation with respect to the crack plane. The latter is a main issue in fiber-reinforced concrete elements, since it significantly influences the structural behavior. The aim of this research is to develop a tailor-made composite material and casting method to orient fibers in order to optimize the performance of the material for structural applications. To this aim, a mechanized concreting device that induces such preferred fiber orientation is designed and fabricated. It uses vibration and a series of narrow channels to guide and orient fibers. A composite with oriented fibers is produced using a hybrid system of macro and micro fibers and high-performance concrete. From the same concrete batch, specimens are cast both with and without the fiber orientation device, obtaining different levels of fiber orientation. Three-point bending tests are performed to measure and compare the residual tensile strength capacities with standard specimens cast according to EN 14651. Elements with favorable fiber orientation show a significant increase in residual tensile strength with respect to the standard beams. Finally, computed tomography and an electromagnetic induction method are employed to better assess the orientation and distribution of fibers in the beams. Their results are in good agreement and enable to link the residual tensile strength parameters with fiber orientation.Item Open Access Computational scatter correction in near real-time with a fast Monte Carlo photon transport model for high-resolution flat-panel CT(2022) Alsaffar, Ammar; Kieß, Steffen; Sun, Kaicong; Simon, SvenIn computed tomography (CT), scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC) simulation is considered the most accurate approach for scatter estimation. However, the existing MC estimators are computationally expensive, especially for high-resolution flat-panel CT. In this paper, we propose a fast and accurate MC photon transport model which describes the physics within the 1 keV to 1 MeV range using multiple controllable key parameters. Based on this model, scatter computation for a single projection can be completed within a range of a few seconds under well-defined model parameters. Smoothing and interpolation are performed on the estimated scatter to accelerate the scatter calculation without compromising accuracy too much compared to measured near scatter-free projection images. Combining the fast scatter estimation with the filtered backprojection (FBP), scatter correction is performed effectively in an iterative manner. To evaluate the proposed MC model, we have conducted extensive experiments on the simulated data and real-world high-resolution flat-panel CT. Compared to the state-of-the-art MC simulators, the proposed MC model achieved a 15 ×acceleration on a single-GPU compared to the GPU implementation of the Penelope simulator (MCGPU) utilizing several acceleration techniques, and a 202 ×speed-up on a multi-GPU system compared to the multi-threaded state-of-the-art EGSnrc MC simulator. Furthermore, it is shown that for high-resolution images, scatter correction with sufficient accuracy is accomplished within one to three iterations using a FBP and the proposed fast MC photon transport model.Item Open Access Multi-material blind beam hardening correction in near real-time based on non-linearity adjustment of projections(2023) Alsaffar, Ammar; Sun, Kaicong; Simon, SvenBeam hardening (BH) is one of the major artifacts that severely reduces the quality of computed tomography (CT) imaging. This BH artifact arises due to the polychromatic nature of the X-ray source and causes cupping and streak artifacts. This work aims to propose a fast and accurate BH correction method that requires no prior knowledge of the materials and corrects first and higher-order BH artifacts. This is achieved by performing a wide sweep of the material based on an experimentally measured look-up table to obtain the closest estimate of the material. Then, the non-linearity effect of the BH is corrected by adding the difference between the estimated monochromatic and the polychromatic simulated projections of the segmented image. The estimated polychromatic projection is accurately derived using the least square estimation (LSE) method by minimizing the difference between the experimental projection and the linear combination of simulated polychromatic projections. As a result, an accurate non-linearity correction term is derived that leads to an accurate BH correction result. The simulated projections in this work are performed using a multi-GPU-accelerated forward projection model which ensures a fast BH correction in near real-time. To evaluate the proposed BH correction method, we have conducted extensive experiments on real-world CT data. It is shown that the proposed method results in images with improved contrast-to-noise ratio (CNR) in comparison to the images corrected from only the scatter artifacts and the BH-corrected images using the state-of-the-art empirical BH correction method.