We propose a hybrid low bit-rate subband video coding scheme utilizing context models, rate-constrained motion estimation and overlapped motion compensation. Emerging efficient context-based entropy coding techniques ...
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We propose a hybrid low bit-rate subband video coding scheme utilizing context models, rate-constrained motion estimation and overlapped motion compensation. Emerging efficient context-based entropy coding techniques fit very well into wavelet/subband-based coding systems, making them very attractive candidates for the entropy coding part of a wavelet/subband-based video coding scheme. A multidimensional probability modeling technique along with context-based entropy coding are utilized to exploit redundancies in the subband structure, yielding better compression.
In this paper, we present a segmented linear subspace model for face recognition that is robust under varying illumination conditions. The algorithm generalizes the 3D illumination subspace model by segmenting the ima...
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ISBN:
(纸本)0769512720
In this paper, we present a segmented linear subspace model for face recognition that is robust under varying illumination conditions. The algorithm generalizes the 3D illumination subspace model by segmenting the image into regions that have surface normals whose directions are close to each other. This segmentation is performed using a K-means clustering algorithm and requires only a few training images under different illuminations. When the linear subspace model is applied to the segmented image, recognition is robust to attached and cast shadows, and the recognition rate is equal to that of computationally more complex systems that require constructing the 3D surface of the face.
In this paper, we investigate the MPEG-2 temporal scalability syntax and introduce a new approach to temporally scalable coding. Temporal scalability is provided by employing various nonlinear prediction and demultipl...
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In this paper, we investigate the MPEG-2 temporal scalability syntax and introduce a new approach to temporally scalable coding. Temporal scalability is provided by employing various nonlinear prediction and demultiplexing schemes. A nonlinear deinterlacing algorithm is presented and the related issues on interlaced, progressive and mixed mode video processing are addressed. In addition to the considered scalability techniques, a lookahead quantization scheme is presented for P- and B-type picture coding, which improves the coding performance by selective combination of the DCT domain scalar quantization and entropy-constrained vector quantization. Remarkable performance improvement over the simulcast coding is achieved.
The traditional sinusoidal transform coder (STC) was originally developed for analysis, synthesis, and modification of speech and other non-polyphonic audio signals. In this paper, a novel method of time-scale modific...
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The traditional sinusoidal transform coder (STC) was originally developed for analysis, synthesis, and modification of speech and other non-polyphonic audio signals. In this paper, a novel method of time-scale modification for polyphonic and multi-pitch audio signals based on STC is proposed. The proposed method does not require a pitch estimation, and as such, it enables STC based algorithms to perform modifications on polyphonic audio signals. The frequency jitter artifacts in the traditional STC are mostly due to the inaccurate onset time estimates measured by pitch periods. The proposed method eliminates the frequency jitter artifacts significantly by using multi-onset time estimations.
For several years, we have been teaching DSP as a first course in electrical and computerengineering at Georgia Tech. Such a dramatic rearrangement of the introductory material requires a new organization of topics a...
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For several years, we have been teaching DSP as a first course in electrical and computerengineering at Georgia Tech. Such a dramatic rearrangement of the introductory material requires a new organization of topics and courses when teaching circuits and systems. In addition, the use of computer-enhanced course materials has a profound impact on the systems courses, which are quite mathematical and abstract in nature. This paper addresses some of the issues encountered when adopting a signalprocessing first approach.
It is shown that the particular form of the frequency support of raw data and focused imagery obtained from an ultra-wideband, wide beamwidth synthetic aperture radar system can be exploited in nonseparable sampling s...
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It is shown that the particular form of the frequency support of raw data and focused imagery obtained from an ultra-wideband, wide beamwidth synthetic aperture radar system can be exploited in nonseparable sampling schemes to reduce the overall amount of raw data samples and image pixels that need to be stored and computed. Furthermore, it is demonstrated that the constant integration angle backprojection (CIAB) image former implicitly applies a fan filter that interpolates raw data sampled on a quincunx grid back onto the underlying rectangular grid. This subtle property of the CIAB has not been exploited so far. It leads to higher quality images with less computational complexity.
This paper presents a time-reversal based approach for detecting the positions of subsurface passive targets like landmines. The measurements are made by using sources and sensors placed on the surface. The imaging al...
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This paper presents a time-reversal based approach for detecting the positions of subsurface passive targets like landmines. The measurements are made by using sources and sensors placed on the surface. The imaging algorithm uses the seismic waves reflected from the targets, and measured on the surface. A time-reversal based algorithm is used, which utilizes the possible link between the time-reversal matrix and the covariance matrix used in standard array processing. It is shown that the time-reversal matrix can be used to estimate the near field DOA and range parameters using a 2D MUSIC approach.
Speech and audio processing algorithms, which are based on the processing of the features and signals, are often written using poor programming styles. Understanding the existing source code and extending it is thus a...
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ISBN:
(纸本)0780365143
Speech and audio processing algorithms, which are based on the processing of the features and signals, are often written using poor programming styles. Understanding the existing source code and extending it is thus a time-consuming process that forces researchers to deal with programming problems instead of speech and audio processing innovations. We have developed a new system in C++ to overcome these problems. The programming techniques used in this environment allow a researcher to concentrate on innovations in an environment that still allows the rapid implementation of efficient real-time speech and audio processing applications.
The sinusoidal transform (ST) provides a sparse representation for speech signals by utilizing several psychoacoustic phenomena. It is well suited to applications in signal enhancement because the signal is represente...
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The sinusoidal transform (ST) provides a sparse representation for speech signals by utilizing several psychoacoustic phenomena. It is well suited to applications in signal enhancement because the signal is represented in a parametric manner that is easy to manipulate. The multi-resolution sinusoidal transform (MRST) has the additional advantage that it is both particularly well suited to typical speech signals and well matched to the human auditory system. The currently reported work discusses the removal of noise from a noisy signal by applying an adaptive Wiener filter to the MRST parameters and then conditioning the parameters to eliminate "musical noise". In informal tests MRST based noise reduction was found to reduce background noise significantly better than traditional Wiener filtering and to virtually eliminate the "musical noise" often associated with Wiener filtering.
Several multidimensional filter banks are described and analyzed for the purpose of processing hyperspectral data. A new octave band directional filter bank (OBDFB) is introduced that is able to isolate directional ba...
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Several multidimensional filter banks are described and analyzed for the purpose of processing hyperspectral data. A new octave band directional filter bank (OBDFB) is introduced that is able to isolate directional bands in three-dimensional Fourier space. The new OBDFB is a maximally decimated exactly reconstructing representation with high computational efficiency. The OBDFB is compared with traditional octave band and uniform band decompositions with respect to compaction and feature identification for analysis.
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