| 1. |
- Andersson, Kenneth, 1970-, et al.
(författare)
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Prediction from off-grid samples using continuous normalized convolution
- 2007
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Ingår i: Signal Processing. - : Elsevier BV. - 0165-1684 .- 1872-7557. ; 87:3, s. 353-365
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.
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| 2. |
- Brun, Anders, 1976-, et al.
(författare)
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A tensor-like representation for averaging, filtering and interpolation of 3D object orientation data
- 2005
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Ingår i: Image Processing, 2005. ICIP 2005. IEEE International Conference on (Volume:3 ). - 0780391349 ; , s. 1092-1095
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Konferensbidrag (refereegranskat)abstract
- Averaging, filtering and interpolation of 3-D object orientation data is important in both computer vision and computer graphics, for instance to smooth estimates of object orientation and interpolate between keyframes in computer animation. In this paper we present a novel framework in which the non-linear nature of these problems is avoided by embedding the manifold of 3-D orientations into a 16-dimensional Euclidean space. Linear operations performed in the new representation can be shown to be rotation invariant, and defining a projection back to the orientation manifold results in optimal estimates with respect to the Euclidean metric. In other words, standard linear filters, interpolators and estimators may be applied to orientation data, without the need for an additional machinery to handle the non-linear nature of the problems. This novel representation also provides a way to express uncertainty in 3-D orientation, analogous to the well known tensor representation for lines and hyperplanes.
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| 3. |
- Brun, Anders, 1976-, et al.
(författare)
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Fast manifold learning based on Riemannian normal coordinates
- 2005
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Ingår i: Image Analysis. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540263203 - 9783540315667 ; , s. 920-
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Konferensbidrag (refereegranskat)abstract
- We present a novel method for manifold learning, i.e. identification of the low-dimensional manifold-like structure present in a set of data points in a possibly high-dimensional space. The main idea is derived from the concept of Riemannian normal coordinates. This coordinate system is in a way a generalization of Cartesian coordinates in Euclidean space. We translate this idea to a cloud of data points in order to perform dimension reduction. Our implementation currently uses Dijkstra’s algorithm for shortest paths in graphs and some basic concepts from differential geometry. We expect this approach to open up new possibilities for analysis of e.g. shape in medical imaging and signal processing of manifold-valued signals, where the coordinate system is “learned” from experimental high-dimensional data rather than defined analytically using e.g. models based on Lie-groups.
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| 4. |
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| 5. |
- Brun, Anders, 1976-, et al.
(författare)
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Intrinsic and Extrinsic Means on the Circle -- a Maximum Likelihood Interpretation
- 2007
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Ingår i: ICASSP 2007. IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. - New York, USA : IEEE. - 1424407273 ; , s. III-1053-III-1056
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Konferensbidrag (refereegranskat)abstract
- For data samples in Rn, the mean is a well known estimator. When the data set belongs to an embedded manifold M in Rn, e.g. the unit circle in R2, the definition of a mean can be extended and constrained to M by choosing either the intrinsic Riemannian metric of the manifold or the extrinsic metric of the embedding space. A common view has been that extrinsic means are approximate solutions to the intrinsic mean problem. This paper study both means on the unit circle and reveal how they are related to the ML estimate of independent samples generated from a Brownian distribution. The conclusion is that on the circle, intrinsic and extrinsic means are maximum likelihood estimators in the limits of high SNR and low SNR respectively
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| 6. |
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| 7. |
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| 8. |
- Brun, Anders, 1976-, et al.
(författare)
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Using Importance Sampling for Bayesian Feature Space Filtering
- 2007
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Ingår i: Proceedings of the 15th Scandinavian conference on image analysis. - Berlin, Heidelberg : Springer-Verlag. - 9783540730392 ; , s. 818-827
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Konferensbidrag (refereegranskat)abstract
- We present a one-pass framework for filtering vector-valued images and unordered sets of data points in an N-dimensional feature space. It is based on a local Bayesian framework, previously developed for scalar images, where estimates are computed using expectation values and histograms. In this paper we extended this framework to handle N-dimensional data. To avoid the curse of dimensionality, it uses importance sampling instead of histograms to represent probability density functions. In this novel computational framework we are able to efficiently filter both vector-valued images and data, similar to e.g. the well-known bilateral, median and mean shift filters.
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| 9. |
- Eriksson-Bylund, Nina, 1971-, et al.
(författare)
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Interactive 3D filter design for ultrasound artifact reduction
- 2005
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Ingår i: Image Processing, 2005. ICIP 2005. IEEE International Conference on (Volume:3 ). - 0780391349 ; , s. 728-731
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Konferensbidrag (refereegranskat)abstract
- A method for detecting and reducing reverberation artifacts in ultrasound image sequences is described. A reverberation artifact localization map is produced using local Rf-bandwidth estimation. To reduce the artifacts an ideal 3D (2D + time) Wiener filter function is computed by using the reverberation map to interactively produce an estimate of the noise and signal spectra. The Wiener filter kernel is optimized to obtain good locality properties. The optimized filter is then applied to the ultrasound image sequence. The test sequence used is from an open chest pig heart, corrupted by strong reverberation artifacts. The selective power of a 3D filter is far superior to that of ID and 2D filters and the reverberation artifacts are almost completely removed by the developed method.
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| 10. |
- Herberthson, Magnus, 1963-, et al.
(författare)
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Pairs of orientation in the plane
- 2006
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Ingår i: SSBA Symposium on Image Analysis,2006. ; , s. 97-100
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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