33,385 research outputs found
Superresolution Enhancement of Hyperspectral CHRIS/Proba Images With a Thin-Plate Spline Nonrigid Transform Model
Given the hyperspectral-oriented waveband configuration of multiangular CHRIS/Proba imagery, the scope of its application could widen if the present 18-m resolution would be improved. The multiangular images of CHRIS could be used as input for superresolution (SR) image reconstruction. A critical procedure in SR is an accurate registration of the low-resolution images. Conventional methods based on affine transformation may not be effective given the local geometric distortion in high off-nadir angular images. This paper examines the use of a non-rigid transform to improve the result of a nonuniform interpolation and deconvolution SR method. A scale-invariant feature transform is used to collect control points (CPs). To ensure the quality of CPs, a rigorous screening procedure is designed: 1) an ambiguity test; 2) the m-estimator sample consensus method; and 3) an iterative method using statistical characteristics of the distribution of random errors. A thin-plate spline (TPS) nonrigid transform is then used for the registration. The proposed registration method is examined with a Delaunay triangulation-based nonuniform interpolation and reconstruction SR method. Our results show that the TPS nonrigid transform allows accurate registration of angular images. SR results obtained from simulated LR images are evaluated using three quantitative measures, namely, relative mean-square error, structural similarity, and edge stability. Compared to the SR methods that use an affine transform, our proposed method performs better with all three evaluation measures. With a higher level of spatial detail, SR-enhanced CHRIS images might be more effective than the original data in various applications.JRC.H.7-Climate Risk Managemen
Robust similarity registration technique for volumetric shapes represented by characteristic functions
This paper proposes a novel similarity registration technique for volumetric shapes implicitly represented by their characteristic functions (CFs). Here, the calculation of rotation parameters is considered as a spherical crosscorrelation problem and the solution is therefore found using the standard phase correlation technique facilitated by principal components analysis (PCA).Thus, fast Fourier transform (FFT) is employed to vastly improve efficiency and robustness. Geometric moments are then used for shape scale estimation which is independent from rotation and translation parameters. It is numericallydemonstrated that our registration method is able to handle shapes with various topologies and robust to noise and initial poses. Further validation of our method is performed by registering a lung database
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
In this paper we present a novel method for the correction of motion
artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of
the whole uterus. Contrary to current slice-to-volume registration (SVR)
methods, requiring an inflexible anatomical enclosure of a single investigated
organ, the proposed patch-to-volume reconstruction (PVR) approach is able to
reconstruct a large field of view of non-rigidly deforming structures. It
relaxes rigid motion assumptions by introducing a specific amount of redundant
information that is exploited with parallelized patch-wise optimization,
super-resolution, and automatic outlier rejection. We further describe and
provide an efficient parallel implementation of PVR allowing its execution
within reasonable time on commercially available graphics processing units
(GPU), enabling its use in the clinical practice. We evaluate PVR's
computational overhead compared to standard methods and observe improved
reconstruction accuracy in presence of affine motion artifacts of approximately
30% compared to conventional SVR in synthetic experiments. Furthermore, we have
evaluated our method qualitatively and quantitatively on real fetal MRI data
subject to maternal breathing and sudden fetal movements. We evaluate
peak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), and
cross correlation (CC) with respect to the originally acquired data and provide
a method for visual inspection of reconstruction uncertainty. With these
experiments we demonstrate successful application of PVR motion compensation to
the whole uterus, the human fetus, and the human placenta.Comment: 10 pages, 13 figures, submitted to IEEE Transactions on Medical
Imaging. v2: wadded funders acknowledgements to preprin
Higher-Order Momentum Distributions and Locally Affine LDDMM Registration
To achieve sparse parametrizations that allows intuitive analysis, we aim to
represent deformation with a basis containing interpretable elements, and we
wish to use elements that have the description capacity to represent the
deformation compactly. To accomplish this, we introduce in this paper
higher-order momentum distributions in the LDDMM registration framework. While
the zeroth order moments previously used in LDDMM only describe local
displacement, the first-order momenta that are proposed here represent a basis
that allows local description of affine transformations and subsequent compact
description of non-translational movement in a globally non-rigid deformation.
The resulting representation contains directly interpretable information from
both mathematical and modeling perspectives. We develop the mathematical
construction of the registration framework with higher-order momenta, we show
the implications for sparse image registration and deformation description, and
we provide examples of how the parametrization enables registration with a very
low number of parameters. The capacity and interpretability of the
parametrization using higher-order momenta lead to natural modeling of
articulated movement, and the method promises to be useful for quantifying
ventricle expansion and progressing atrophy during Alzheimer's disease
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