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Highway tunnel environment is dim, with the interaction of multi-color light sources, which forms a light haze. Such a complicated scene makes the image blurred and arouses difficulties in the image enhancement. According to the law of haze imaging, a haze removal algorithm for nighttime scene is applied to enhance the tunnel image in this paper. First, the global atmospheric light is estimated as...
A cryo Electron Microscopy dataset is composed on tomographic projections of an object (e.g. a macromolecule). The projection orientation information is unknown. The scope of this paper is the projection parameterization in the case of a deformable object. An overview of the parametrization methods is presented. Then a new approach based on manifold learning is detailed. Finally, an evaluation method...
In urban areas, the reconstruction of gable-roof buildings from high-resolution synthetic aperture radar (SAR) images is more challenging compared to simple parallelepiped buildings. In this paper, an alternate iteration and matching technique is proposed for height and roof inclination angle estimation of gable-roof buildings. First, the different appearances of this building type in SAR images are...
In this study, we consider tree vertical profile with a higher order truncation of Fourier-Legendre series using polarization coherence tomography. An improved method based on Freeman-Durben decomposition is employed to estimate tree height and surface phase. A contrast to single-baseline scenario is performed. The primary scattering mechanisms and polarization dependence are interpreted by vertical...
Positron Emission Tomography (PET) is a powerful tool for patient diagnosis and assessment of therapy response, which is carried out through comparison of PET measurements from longitudinal scans. However, as with any measurement tool, an estimate of error or uncertainty is required for meaningful comparison of such measurements. We have developed a bootstrap-based method for estimating uncertainty...
This paper presents a novel colon fold contour estimation technique, a crucial step toward fully-automated reconstruction of a 3D colon segment from an image captured from colonoscopy for automated labeling of unseen mucosa areas (where polyps or abnormal lesions may reside) during colonoscopy. The endoscopist can then manipulate the endoscope to inspect these unseen areas. The proposed technique...
We are interested in image reconstruction when data provided by several sensors are corrupted with a linear operator and an additive white Gaussian noise. This problem is addressed by invoking Stein's Unbiased Risk Estimate (SURE) techniques. The key advantage of SURE methods is that they do not require prior knowledge about the statistics of the unknown image, while yielding an expression of the...
The success of restoring images degraded by motion blur highly depends on precise estimation of parameters such as motion direction and length that were involved in the motion Point Spread Function (PSF). This paper presents a new method for determination of linear motion point spread function for automatic restoration of an image. The method assumes a spatially invariant linear blur over the image...
We propose new estimation methods for the Ising field parameter based on an explicit expression for the partition function. This expression is known for a long time, but, to the best of our knowledge, it has never been used for parameter estimation. The paper develops standard Bayesian estimates and proposes a numerical comparative evaluation.
In human body pose estimation, manifold learning is a popular technique for reducing the dimension of 2D images and 3D body configuration data. This technique, however, is especially vulnerable to silhouette variation such as caused by viewpoint changes. In this paper, we propose a novel approach that combines three separate manifolds for representing variations in viewpoint, pose and 3D body configuration...
Traditional magnetic resonance imaging (MRI) studies are based on image contrast and qualitative analysis. However, there is an increasing interest in quantifying the physical parameters of the object such as the free induction decay rate, T*2 . In this paper, a new Bayesian algorithm is proposed for the estimation of T*2 from gradient echo MRI scans. Current estimation methods use a simple signal...
A minimum-phase method (MPM) is approved on a set of radioholographic test objects. Objects' parameters estimations' classification characteristics, their bias and variance as the function of signal-to-noise ratio (SNR) are obtained.
In modern driver assistance systems the environment perception plays a decisive role in order to evaluate the current traffic scene. The reliable recognition of the drivable area provides essential information for lane departure warning systems which in turn contribute to active road safety. Most systems on lane recognition do reliable work on well marked roads and under good weather and lighting...
We describe a method to directly estimate Patlak parameters from list mode data. Based on the Patlak model, the uptake rate function of each voxel can be written as a linear combination of the blood input function and its integral, with the slope and intercept of the Patlak model as the corresponding weight. The positron emission rate in each voxel is then modeled as an inhomogeneous Poisson process...
Quantitative MR imaging experiments (e.g., to measure relaxation and diffusion properties of tissues) often require image sequences with different contrast in each frame. However, high-resolution acquisition of each frame can lead to prohibitively long experiments. In this work, we investigate the possibility of utilizing a parametric contrast model to synthesize high-resolution information. Theoretical...
For the purpose of motion-compensated processing we propose a temporal modeling approach for determining the image motion in a gated cardiac sequence, wherein the inherent image motion is periodic over time. To exploit the periodic nature of the cardiac motion, we use a Fourier harmonic representation to describe the motion field for the entire sequence. We then determine the motion field by estimating...
MPEG coded video may be processed for quality assessment or postprocessed to reduce coding artifacts or transcoded. Utilizing information about the MPEG stream may be useful for these tasks. This paper deals with estimating MPEG parameter information from the decoded video stream without access to the MPEG stream. This may be used in systems and applications where the coded stream is not accessible...
Estimation of a parametric 2D spatial target model is proposed in this paper, with ultimate goal to support radar target classification. Limited number of multi-aspect High Range Resolution (HRR) data from a radar network are used as source of information. Back-projection in 2D space and mixture model fitting is applied for the estimation. The ghosts are progressively resolved and unambiguous retrieval...
We propose a temporal modeling approach for determining image motion from a sequence of images within which the inherent motion is periodic. To exploit the periodic nature of the motion, we use a Fourier harmonic representation to model the motion field for the entire sequence. We then determine the motion field by estimating the parameters of this representation model. This joint estimation approach...
Linear inverse problems in computer vision, including motion estimation, shape fitting and image reconstruction, give rise to parameter estimation problems with highly correlated errors in variables. Established total least squares methods estimate the most likely corrections Acirc and bcirc to a given data matrix [A, b] perturbed by additive Gaussian noise, such that there exists a solution y with...
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