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538
ThreeDimensional Embedded Subband Coding with Optimized Truncation (3D ESCOT)
 3D ESCOT)”, Applied and Computational Harmonic Analysis10
, 2001
"... This paper presents an efficient video coding algorithm: Threedimensional embedded subband coding with optimized truncation (3D ESCOT), in which coefficients in different subbands are independently coded using fractional bitplane coding and candidate truncation points are formed at the end of ..."
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Cited by 58 (20 self)
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This paper presents an efficient video coding algorithm: Threedimensional embedded subband coding with optimized truncation (3D ESCOT), in which coefficients in different subbands are independently coded using fractional bitplane coding and candidate truncation points are formed at the end of each fractional bitplane. A ratedistortion optimized truncation scheme is used to multiplex all subband bitstreams together into a layered one. A novel motion threading technique is proposed to form threads along the motion trajectories in a scene. For efficient coding of motion threads, memoryconstrained temporal wavelet transforms are applied along entire motion threads. Blockbased motion threading is implemented in conjunction with 3D ESCOT in a real video coder. Extension of 3D ESCOT to objectbased coding is also addressed. Experiments demonstrate that 3D ESCOT outperforms MPEG4 for most test sequences at the same bit rate. # 2001 Academic Press 1.
Generalized FFTs  A Survey Of Some Recent Results
, 1995
"... In this paper we survey some recent work directed towards generalizing the fast Fourier transform (FFT). We work primarily from the point of view of group representation theory. In this setting the classical FFT can be viewed as a family of efficient algorithms for computing the Fourier transform of ..."
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Cited by 57 (7 self)
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In this paper we survey some recent work directed towards generalizing the fast Fourier transform (FFT). We work primarily from the point of view of group representation theory. In this setting the classical FFT can be viewed as a family of efficient algorithms for computing the Fourier transform of either a function defined on a finite abelian group, or a bandlimited function on a compact abelian group. We discuss generalizations of the FFT to arbitrary finite groups and compact Lie groups.
Interpolation based transmit beamforming for MIMOOFDM with limited feedback,” in
 Proc. IEEE Int. Conf. on Communications,
, 2004
"... AbstractTransmit beamforming with receive combining is a simple method for exploiting the significant diversity provided by multipleinput multipleoutput (MIMO) systems, and the use of orthogonal frequency division multiplexing (OFDM) enables low complexity implementation of this scheme over freq ..."
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Cited by 53 (4 self)
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AbstractTransmit beamforming with receive combining is a simple method for exploiting the significant diversity provided by multipleinput multipleoutput (MIMO) systems, and the use of orthogonal frequency division multiplexing (OFDM) enables low complexity implementation of this scheme over frequency selective MIMO channels. This paper proposes a beamforming technique that reduces feedback requirements for optimal beamforming. In the proposed architecture, the receiver sends back quantized versions of select beamforming vectors and the transmitter reconstructs the missing beamforming vectors through interpolation. Since a beamforming vector is phase invariant and has unit norm, a new spherical linear interpolator is proposed that exploits additional parameters for phase rotation. These parameters are determined at the receiver in the sense of maximizing the minimum channel gain or capacity, and sent back to the transmitter along with the quantized beamforming vectors. Simulation results show that the proposed beamforming method requires much less feedback information than optimal beamforming with only slight diversity loss.
Amplitude Modulation Decorrelation For Convolutive Blind Source Separation
 Proc. Second international workshop on
, 2000
"... The problem of blind separation of a convolutive mixture of speech signals is considered. Signal separation is performed in the frequency domain. Based on observations from amplitude spectrograms of speech signals, the notion of amplitude modulation correlation (`AMCor') across dierent frequen ..."
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Cited by 51 (1 self)
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The problem of blind separation of a convolutive mixture of speech signals is considered. Signal separation is performed in the frequency domain. Based on observations from amplitude spectrograms of speech signals, the notion of amplitude modulation correlation (`AMCor') across dierent frequency channels is introduced. From the corresponding principle of amplitude modulation decorrelation, a novel costfunction and an algorithm for convolutive blind source separation are derived. The algorithms' main features are discussed. Successful separation of synthetic data and of realroom recordings of speech is performed. The results of the latter are compared to the performance of previous algorithms on the same data. Audio examples are available from the authors' web page [2]. In: P. Pajunen and J. Karhunen (Eds.), `Proceedings of the second international workshop on independent component analysis and blind signal separation', June 1922, 2000, Helsinki, Finland, pp. 215220. 1. INTRODU...
Fast Discrete Polynomial Transforms with Applications to Data Analysis for Distance Transitive Graphs
, 1997
"... . Let P = fP 0 ; : : : ; Pn\Gamma1 g denote a set of polynomials with complex coefficients. Let Z = fz 0 ; : : : ; z n\Gamma1 g ae C denote any set of sample points. For any f = (f 0 ; : : : ; fn\Gamma1 ) 2 C n the discrete polynomial transform of f (with respect to P and Z) is defined as the col ..."
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Cited by 47 (9 self)
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. Let P = fP 0 ; : : : ; Pn\Gamma1 g denote a set of polynomials with complex coefficients. Let Z = fz 0 ; : : : ; z n\Gamma1 g ae C denote any set of sample points. For any f = (f 0 ; : : : ; fn\Gamma1 ) 2 C n the discrete polynomial transform of f (with respect to P and Z) is defined as the collection of sums, f b f(P 0 ); : : : ; b f(Pn\Gamma1 )g, where f(P j ) = hf; P j i = P n\Gamma1 i=0 f i P j (z i )w(i) for some associated weight function w. These sorts of transforms find important applications in areas such as medical imaging and signal processing. In this paper we present fast algorithms for computing discrete orthogonal polynomial transforms. For a system of N orthogonal polynomials of degree at most N \Gamma 1 we give an O(N log 2 N) algorithm for computing a discrete polynomial transform at an arbitrary set of points instead of the N 2 operations required by direct evaluation. Our algorithm depends only on the fact that orthogonal polynomial sets satisfy a thre...
Frame Representations for Texture Segmentation
 IEEE Transactions on Image Processing
, 1996
"... We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and twodimensional envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zerocrossings. We present criteria ..."
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Cited by 44 (1 self)
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We introduce a novel method of feature extraction for texture segmentation that relies on multichannel wavelet frames and twodimensional envelope detection. We describe and compare two algorithms for envelope detection based on (1) the Hilbert transform and (2) zerocrossings. We present criteria for filter selection and discuss quantitatively their effect on feature extraction. The performance of our method is demonstrated experimentally on samples of both natural and synthetic textures. Keywords Feature extraction, image segmentation, wavelet analysis. I. Introduction Features for texture representation are of crucial importance for accomplishing segmentation[1]. Previous multichannel approaches for texture feature extraction utilized the concept of spatialfrequency representation [2] [3], and have been supported by studies of the human visual system [4]. In these methods, both complex and real filters were used. Complex prolate spheroidal sequences were used as channel filter...
Understanding Dynamic Scenes
, 2000
"... We propose a framework for the representation of visual knowledge in a robotic agent, with special attention to the understanding of dynamic scenes. According to our approach, understanding involves the generation of a high level, declarative description of the perceived world. Developing such a des ..."
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Cited by 44 (12 self)
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We propose a framework for the representation of visual knowledge in a robotic agent, with special attention to the understanding of dynamic scenes. According to our approach, understanding involves the generation of a high level, declarative description of the perceived world. Developing such a description requires both bottomup, data driven processes that associate symbolic knowledge representation structures with the data coming out of a vision system, and topdown processes in which high level, symbolic information is in its turn employed to drive and further refine the interpretation of a scene. On the one hand, the computer vision community approached this problem in terms of 2D/3D shape reconstruction and of estimation of motion parameters. On the other, the AI community developed rich and expressive systems for the description of processes, events, actions and, in general, of dynamic situations. Nevertheless, these two approaches evolved separately and concentrated on different kinds of problems. We propose an architecture that integrates these two traditions in a principled way. Our assumption is that a link is missing between the two classes of representations mentioned above. In order to fill this gap, we adopt the notion of conceptual space (CSGärdenfors [58]), a representation where information is characterized in terms of a metric space. A CS acts as an intermediate representation between subconceptual (i.e., not yet conceptually categorized) information, and symbolically organized knowledge. The concepts of process and action have immediate characterizations in terms of structures in the conceptual space. The architecture is illustrated with reference to an experimental setup based on a vision system operating in a scenario with moving and interacting people.
A new method based on spectral subtraction for speech dereverberation
 Acta Acoust
, 2001
"... A new monaural method for the suppression of late room reverberation from speech signals, based on spectral subtraction, is presented. The problem of reverberation suppression differs from classical speech denoising in that the “reverberation noise ” is non stationary. In this paper, the use of a n ..."
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Cited by 43 (0 self)
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A new monaural method for the suppression of late room reverberation from speech signals, based on spectral subtraction, is presented. The problem of reverberation suppression differs from classical speech denoising in that the “reverberation noise ” is non stationary. In this paper, the use of a novel estimator of the nonstationary reverberationnoise power spectrum, based on a statistical model of late reverberation, is presented. The algorithm is tested on real reverberated signals. The performances for different RIRs with ranging from 0.34 s to 1.7 s consistently show significant noise reduction with little signal distortion. Moreover, when used as a front end to an automatic speech recognition system, the algorithm brings about dramatic improvements in terms of automatic speech recognition scores in various reverberant environments. PACS no. 43.00.Xx, 00.00.Xx 1.
Linear and Cubic Box Splines for the Body Centered Cubic Lattice
 In Proceedings of the IEEE Conference on Visualization
, 2004
"... In this paper we derive piecewise linear and piecewise cubic box spline reconstruction filters for data sampled on the body centered cubic (BCC) lattice. We analytically derive a time domain representation of these reconstruction filters and using the Fourier sliceprojection theorem we derive their ..."
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Cited by 41 (8 self)
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In this paper we derive piecewise linear and piecewise cubic box spline reconstruction filters for data sampled on the body centered cubic (BCC) lattice. We analytically derive a time domain representation of these reconstruction filters and using the Fourier sliceprojection theorem we derive their frequency responses. The quality of these filters, when used in reconstructing BCC sampled volumetric data, is discussed and is demonstrated with a raycaster. Moreover, to demonstrate the superiority of the BCC sampling, the resulting reconstructions are compared with those produced from similar filters applied to data sampled on the Cartesian lattice.