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4,292
Efficient time series matching by wavelets
 Proc. of 15th Int'l Conf. on Data Engineering
, 1999
"... Time series stored as feature vectors can be indexed by multidimensional index trees like RTrees for fast retrieval. Due to the dimensionality curse problem, transformations are applied to time series to reduce the number of dimensions of the feature vectors. Different transformations like Discrete ..."
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Cited by 286 (1 self)
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Discrete Fourier Transform (DFT), Discrete Wavelet Transform (DWT), KarhunenLoeve (KL) transform or Singular Value Decomposition (SVD) can be applied. While the use of DFT and KL transform or SVD have been studied in the literature, to our knowledge, there is no indepth study on the application of DWT
Fourier Transform
"... The vast majority of previous work in noise reduction for visual media has assumed uncorrelated, white, noise sources. In practice this is almost always violated by real media. Film grain noise is never white, and this paper highlights that the same applies to almost all consumer video content. We t ..."
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reduction in the Fourier frequency domain. Results show improved performance for noise reduction in an easily pipelined system.
SPIRAL: Code Generation for DSP Transforms
 PROCEEDINGS OF THE IEEE SPECIAL ISSUE ON PROGRAM GENERATION, OPTIMIZATION, AND ADAPTATION
"... Fast changing, increasingly complex, and diverse computing platforms pose central problems in scientific computing: How to achieve, with reasonable effort, portable optimal performance? We present SPIRAL that considers this problem for the performancecritical domain of linear digital signal proces ..."
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Cited by 222 (41 self)
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processing (DSP) transforms. For a specified transform, SPIRAL automatically generates high performance code that is tuned to the given platform. SPIRAL formulates the tuning as an optimization problem, and exploits the domainspecific mathematical structure of transform algorithms to implement a feedback
Image compression via joint statistical characterization in the wavelet domain
, 1997
"... We develop a statistical characterization of natural images in the wavelet transform domain. This characterization describes the joint statistics between pairs of subband coefficients at adjacent spatial locations, orientations, and scales. We observe that the raw coefficients are nearly decorrelate ..."
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Cited by 238 (24 self)
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We develop a statistical characterization of natural images in the wavelet transform domain. This characterization describes the joint statistics between pairs of subband coefficients at adjacent spatial locations, orientations, and scales. We observe that the raw coefficients are nearly
Fast Fourier transforms for nonequispaced data: A tutorial
, 2000
"... In this section, we consider approximative methods for the fast computation of multivariate discrete Fourier transforms for nonequispaced data (NDFT) in the time domain and in the frequency domain. In particular, we are interested in the approximation error as function of the arithmetic complexity o ..."
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Cited by 142 (30 self)
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In this section, we consider approximative methods for the fast computation of multivariate discrete Fourier transforms for nonequispaced data (NDFT) in the time domain and in the frequency domain. In particular, we are interested in the approximation error as function of the arithmetic complexity
Spatial prediction filtering in the fractional Fourier domain
"... The fractional Fourier transform is a new concept in the theory of timefrequency representations. Closely linked to the Wigner distribution through the Radon transform, it introduces frequencytime hybrid domains in which the signal and the noise could be interwoven differently than in either the t ..."
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The fractional Fourier transform is a new concept in the theory of timefrequency representations. Closely linked to the Wigner distribution through the Radon transform, it introduces frequencytime hybrid domains in which the signal and the noise could be interwoven differently than in either
Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases
, 2000
"... The problem of similarity search in large time series databases has attracted much attention recently. It is a nontrivial problem because of the inherent high dimensionality of the data. The most promising solutions involve first performing dimensionality reduction on the data, and then indexing th ..."
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Cited by 240 (21 self)
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the reduced data with a spatial access method. Three major dimensionality reduction techniques have been proposed, Singular Value Decomposition (SVD), the Discrete Fourier transform (DFT), and more recently the Discrete Wavelet Transform (DWT). In this work we introduce a new dimensionality reduction
Action MACH: a spatiotemporal maximum average correlation height filter for action recognition
 In Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition
, 2008
"... In this paper we introduce a templatebased method for recognizing human actions called Action MACH. Our approach is based on a Maximum Average Correlation Height (MACH) filter. A common limitation of templatebased methods is their inability to generate a single template using a collection of examp ..."
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Cited by 237 (10 self)
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avoid the high computational cost commonly incurred in templatebased approaches. Vector valued data is analyzed using the Clifford Fourier transform, a generalization of the Fourier transform intended for both scalar and vectorvalued data. Finally, we perform an extensive set of experiments
Fourier volume rendering
 ACM Transactions on Graphics
, 1993
"... In computer graphics we have traditionally rendered images of data sets specified spatially, Here, we present a volume rendering technique that operates on a frequency domain representation of the data set and that efficiently generates line integral projections of the spatial data it represents, Th ..."
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Cited by 131 (1 self)
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In computer graphics we have traditionally rendered images of data sets specified spatially, Here, we present a volume rendering technique that operates on a frequency domain representation of the data set and that efficiently generates line integral projections of the spatial data it represents
OPTICS COMMUNICATIONS Fractional Fourier transform applied to spatial filtering in the Fresnel domain
, 1994
"... The fractional Fourier transform can be optically defined through a phasespace coordinate rotation of the Wigner distribution function associated with the input signal. This operation can be achieved by performing three successive shearing processes, which are reduced to a freespace Fresnel diffra ..."
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integrals. Thus, the diffraction process leads to a Fourier transform relationship, operation which is the basis for developing spatial filtering devices. On the other hand, for a quadratic graded index (GRIN) medium the amplitude distribution at different locations along the propagation axis can
Results 11  20
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4,292