45 resultados para Subpixel
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Purpose: To quantify the uncertainties of carotid plaque morphology reconstruction based on patient-specific multispectral in vivo magnetic resonance imaging (MRI) and their impacts on the plaque stress analysis. Materials and Methods: In this study, three independent investigators were invited to reconstruct the carotid bifurcation with plaque based on MR images from two subjects to study the geometry reconstruction reproducibility. Finite element stress analyses were performed on the carotid bifurcations, as well as the models with artificially modified plaque geometries to mimic the image segmentation uncertainties, to study the impacts of the uncertainties to the stress prediction. Results: Plaque reconstruction reproducibility was generally high in the study. The uncertainties among interobservers are around one or the subpixel level. It also shows that the predicted stress is relatively less sensitive to the arterial wall segmentation uncertainties, and more affected by the accuracy of lipid region definition. For a model with lipid core region artificially increased by adding one pixel on the lipid region boundary, it will significantly increase the maximum Von Mises Stress in fibrous cap (>100%) compared with the baseline model for all subjects. Conclusion: The current in vivo MRI in the carotid plaque could provide useful and reliable information for plaque morphology. The accuracy of stress analysis based on plaque geometry is subject to MRI quality. The improved resolution/quality in plaque imaging with newly developed MRI protocols would generate more realistic stress predictions.
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It was demonstrated in earlier work that, by approximating its range kernel using shiftable functions, the nonlinear bilateral filter can be computed using a series of fast convolutions. Previous approaches based on shiftable approximation have, however, been restricted to Gaussian range kernels. In this work, we propose a novel approximation that can be applied to any range kernel, provided it has a pointwise-convergent Fourier series. More specifically, we propose to approximate the Gaussian range kernel of the bilateral filter using a Fourier basis, where the coefficients of the basis are obtained by solving a series of least-squares problems. The coefficients can be efficiently computed using a recursive form of the QR decomposition. By controlling the cardinality of the Fourier basis, we can obtain a good tradeoff between the run-time and the filtering accuracy. In particular, we are able to guarantee subpixel accuracy for the overall filtering, which is not provided by the most existing methods for fast bilateral filtering. We present simulation results to demonstrate the speed and accuracy of the proposed algorithm.
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A modular image capture system with close integration to CCD cameras has been developed. The aim is to produce a system capable of integrating CCD sensor, image capture and image processing into a single compact unit. This close integration provides a direct mapping between CCD pixels and digital image pixels. The system has been interfaced to a digital signal processor board for the development and control of image processing tasks. These have included characterization and enhancement of noisy images from an intensified camera and measurement to subpixel resolutions. A highly compact form of the image capture system is in an advanced stage of development. This consists of a single FPGA device and a single VRAM providing a two chip image capturing system capable of being integrated into a CCD camera. A miniature compact PC has been developed using a novel modular interconnection technique, providing a processing unit in a three dimensional format highly suited to integration into a CCD camera unit. Work is under way to interface the compact capture system to the PC using this interconnection technique, combining CCD sensor, image capture and image processing into a single compact unit. ©2005 Copyright SPIE - The International Society for Optical Engineering.
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We present a model for early vision tasks such as denoising, super-resolution, deblurring, and demosaicing. The model provides a resolution-independent representation of discrete images which admits a truly rotationally invariant prior. The model generalizes several existing approaches: variational methods, finite element methods, and discrete random fields. The primary contribution is a novel energy functional which has not previously been written down, which combines the discrete measurements from pixels with a continuous-domain world viewed through continous-domain point-spread functions. The value of the functional is that simple priors (such as total variation and generalizations) on the continous-domain world become realistic priors on the sampled images. We show that despite its apparent complexity, optimization of this model depends on just a few computational primitives, which although tedious to derive, can now be reused in many domains. We define a set of optimization algorithms which greatly overcome the apparent complexity of this model, and make possible its practical application. New experimental results include infinite-resolution upsampling, and a method for obtaining subpixel superpixels. © 2012 IEEE.
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The article discusses the progress and issues related to transparent oxide semiconductor (TOS) TFTs for advanced display and imaging applications. Amorphous oxide semiconductors continue to spark new technological developments in transparent electronics on a multitude of non-conventional substrates. Applications range from high-frame-rate interactive displays with embedded imaging to flexible electronics, where speed and transparency are essential requirements. TOS TFTs exhibit high transparency as well as high electron mobility even when fabricated at room temperature. Compared to conventional a-Si TFT technology, TOS TFTs have higher mobility and sufficiently good uniformity over large areas, similar in many ways to LTPS TFTs. Moreover, because the amorphous oxide semiconductor has higher mobility compared to that of conventional a-Si TFT technology, this allows higher-frame-rate display operation. This would greatly benefit OLED displays in particular because of the need for lower-cost higher-mobility analog circuits at every subpixel.
Resumo:
针对目前焊缝坐标提取方法存在精度较低,难于实现视觉引导的机器人激光焊接高速度、高精度的要求,提出一种基于Zernike正交矩的曲线焊缝位置坐标信息获取算法,该算法首先采用Zernike边缘检测算法识别焊缝边缘,然后提取出焊缝的中心线,最后计算出该中心线的亚像素坐标。通过试验验证了该算法的可行性。
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介绍了Zernike矩及基于Zernike矩的图像亚像素边缘检测原理,针对Ghosal提出的基于Zernike矩的亚像素图像边缘检测算法检测出的图像存在边缘较粗及边缘亚像素定位精度低等不足,提出了一种改进算法.推导了7×7 Zernike矩模板系数,提出一种新的边缘判断依据.改进的算法能较好检测图像边缘并实现了较高的边缘定位.最后,设计了3组不同的实验.实验结果同Canny算子及Ghosal算法相比,证明了改进算法的优越性.
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CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the “early vision” stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.
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The search for the progenitors of six core-collapse supernovae (CCSNe) in archival Hubble Space Telescope (HST) WFPC2 pre-explosion imaging is presented. These SNe are 1999an, 1999br, 1999ev, 2000ds, 2000ew and 2001B. Post-explosion imaging of the SNe, with the HST ACS/WFC, has been utilized with the technique of differential astrometry to identify the progenitor locations on the pre-explosion imaging. SNe 1999br, 1999ev, 2000ew and 2001B are recovered in late-time imaging, and estimates of the progenitor locations on the pre-explosion imaging, with subpixel accuracy, have been made. Only the progenitor of the Type II-P SN 1999ev has been recovered, on pre-explosion F555W imaging, at a 4.8 sigma significance level. Assuming a red supergiant progenitor, the pre-explosion observation is consistent with M-ZAMS = 15-18 M-circle dot. The progenitors of the other five SNe were below the 3 sigma detection threshold of the pre-explosion observations. The detection thresholds were translated to mass limits for the progenitors by comparison with stellar evolution models. Pre-explosion observations of the peculiarly faint SN 1999br limit the mass of a red supergiant progenitor to M-ZAMS
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We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, and also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide corrections from a series of science images and recentre telescope pointing between each exposure. The algorithm has the unique ability of calculating guide corrections from undersampled to heavily defocused point spread functions. We present the case for why such an algorithm is important for high precision photometry and give our results from off and on-sky testing. We discuss the limitations of DONUTS and the facilities where it soon will be deployed.
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A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.
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Cette thèse porte sur la reconstruction active de modèles 3D à l’aide d’une caméra et d’un projecteur. Les méthodes de reconstruction standards utilisent des motifs de lumière codée qui ont leurs forces et leurs faiblesses. Nous introduisons de nouveaux motifs basés sur la lumière non structurée afin de pallier aux manques des méthodes existantes. Les travaux présentés s’articulent autour de trois axes : la robustesse, la précision et finalement la comparaison des patrons de lumière non structurée aux autres méthodes. Les patrons de lumière non structurée se différencient en premier lieu par leur robustesse aux interréflexions et aux discontinuités de profondeur. Ils sont conçus de sorte à homogénéiser la quantité d’illumination indirecte causée par la projection sur des surfaces difficiles. En contrepartie, la mise en correspondance des images projetées et capturées est plus complexe qu’avec les méthodes dites structurées. Une méthode d’appariement probabiliste et efficace est proposée afin de résoudre ce problème. Un autre aspect important des reconstructions basées sur la lumière non structurée est la capacité de retrouver des correspondances sous-pixels, c’est-à-dire à un niveau de précision plus fin que le pixel. Nous présentons une méthode de génération de code de très grande longueur à partir des motifs de lumière non structurée. Ces codes ont l’avantage double de permettre l’extraction de correspondances plus précises tout en requérant l’utilisation de moins d’images. Cette contribution place notre méthode parmi les meilleures au niveau de la précision tout en garantissant une très bonne robustesse. Finalement, la dernière partie de cette thèse s’intéresse à la comparaison des méthodes existantes, en particulier sur la relation entre la quantité d’images projetées et la qualité de la reconstruction. Bien que certaines méthodes nécessitent un nombre constant d’images, d’autres, comme la nôtre, peuvent se contenter d’en utiliser moins aux dépens d’une qualité moindre. Nous proposons une méthode simple pour établir une correspondance optimale pouvant servir de référence à des fins de comparaison. Enfin, nous présentons des méthodes hybrides qui donnent de très bons résultats avec peu d’images.
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When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system
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This paper presents a unique two-stage image restoration framework especially for further application of a novel rectangular poor-pixels detector, which, with properties of miniature size, light weight and low power consumption, has great value in the micro vision system. To meet the demand of fast processing, only a few measured images shifted up to subpixel level are needed to join the fusion operation, fewer than those required in traditional approaches. By maximum likelihood estimation with a least squares method, a preliminary restored image is linearly interpolated. After noise removal via Canny operator based level set evolution, the final high-quality restored image is achieved. Experimental results demonstrate effectiveness of the proposed framework. It is a sensible step towards subsequent image understanding and object identification.
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Optimized experimental conditions for extracting accurate information at subpixel length scales from analyzer-based X-ray imaging were obtained and applied to investigate bone regeneration by means of synthetic beta-TCP grafting materials in a rat calvaria model. The results showed a 30% growth in the particulate size due to bone ongrowth/ingrowth within the critical size defect over a 1-month healing period.