This paper is concerned with reducing the rank of the adaptive weight vector in radar array signal processing. The motivation for reducing the rank is that modern space-time processing requires many more weights than ...
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Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of v...
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Video parsing is a fundamental operation used in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the parsing algorithm is critical if large amounts of video data are to be processed, particularly in real-time. We present a new algorithm to reconstruct DC coefficient images of a DCT and motion compensation compressed video sequence, e.g. MPEG. The histograms of the DC coefficient images can be used to detect scene changes.
In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. T...
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In this paper we describe two error-recovery approaches for MPEG encoded video over ATM networks. The first approach aims at reconstructing each lost pixel by spatial interpolation from the nearest undamaged pixels. The second approach recovers lost macroblocks by minimizing intersample variations within each block and across its boundaries. Moreover, a new technique for packing ATM cells with compressed data is also proposed.
We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions...
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We describe a multiresolution approach to edge detection using a sequential search algorithm. The use of a multiresolution image pyramid allows the integration of global edge information contained in lower resolutions to guide the sequential search at higher resolutions. As a consequence, the dependence on a priori knowledge of the image edges is greatly reduced. Estimating the sequential search parameters from lower resolution images provides for a more accurate and less costly search of edge paths in the image.
A nonlinear method for image interpolation is presented based on spatial domain directional interpolation. Existing directional interpolation algorithms, which only consider edge regions, are extended to the whole ima...
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A nonlinear method for image interpolation is presented based on spatial domain directional interpolation. Existing directional interpolation algorithms, which only consider edge regions, are extended to the whole image by interpolating in multiple directions. The interpolated values along various directions are combined using directional weights, which depend on the variation in that direction. The interpolation value for each direction is assigned based on the magnitude of its directional derivative.
We show that an archetypal nonlinear chaotic system can be interpreted as a first order anticausal IIR filter stimulated by i.i.d. Bernoulli noise. Based on this interpretation, we develop and characterize a number of...
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We show that an archetypal nonlinear chaotic system can be interpreted as a first order anticausal IIR filter stimulated by i.i.d. Bernoulli noise. Based on this interpretation, we develop and characterize a number of estimators for the system, all of which perform poorly in high levels of noise. We hypothesize that when the noise-imposed channel capacity falls below the information production rate of the chaotic system no estimator can deduce the system's underlying state. To provide direct evidence for this hypothesis, we compute the mutual information between the state and the corresponding noise-corrupted observations and demonstrate that at small signal-to-noise ratios the observations do not contain enough information about the state to accurately determine its value.
A rate distortion constrained statistical motion estimation algorithm is presented that leads to improvements in subband video coding. The main advantages of the algorithm is that it requires a relatively small number...
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A rate distortion constrained statistical motion estimation algorithm is presented that leads to improvements in subband video coding. The main advantages of the algorithm is that it requires a relatively small number of computations, produces a much smoother motion field, and employs a more effective measure of performance than the conventional mean absolute difference or mean squared error. The proposed algorithm circumvents problems in the motion compensation loop such as illumination variations, noise, and occlusions, by providing a mechanism for alternating between intraframe and residual coding. Experimental results demonstrate that the corresponding video coder outperforms the H.263 in terms of motion vector search complexity and overall bit rate at the same reproduction quality.
An iterative method for reducing noise in contaminated chaotic signals is proposed. This method estimates the deviation of the observed signal from the nearest noise-free signal satisfying the system dynamics in order...
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An iterative method for reducing noise in contaminated chaotic signals is proposed. This method estimates the deviation of the observed signal from the nearest noise-free signal satisfying the system dynamics in order to get a noise-reduced (or enhanced) signal. To calculate the deviation we minimize a cost function composed of two parts: one containing information that represents how close the enhanced signal is to the observed signal and another including constraints that fit the dynamics of the system. This method has a simple structure and is flexible in the choice of the parts of the cost function. The proposed method is compared with Farmer's method which is known to have good performance in mild signal-to-noise ratios but has a more complex structure.
Sampling and reconstruction are usually analyzed under the framework of linear signal processing. Powerful tools like the Fourier transform and optimum linear filter design techniques, allow for a very precise analysi...
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Sampling and reconstruction are usually analyzed under the framework of linear signal processing. Powerful tools like the Fourier transform and optimum linear filter design techniques, allow for a very precise analysis of the process. In particular, an optimum linear filter of any length can be derived under most situations. Many of these tools are not available for non-linear systems, and it is usually difficult to find an optimum non-linear system under any criteria. The authors analyze the possibility of using non-linear filtering in the interpolation of subsampled images. They show that a very simple (5/spl times/5) non-linear reconstruction filter outperforms (for the images analyzed) linear filters of up to 256/spl times/256, including optimum (separable) Wiener filters of any size.
A secure communication scheme using a chaotic system is presented. The noise-like properties of chaotic signals has been exploited previously for secure communications. However, because previous methods require very h...
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A secure communication scheme using a chaotic system is presented. The noise-like properties of chaotic signals has been exploited previously for secure communications. However, because previous methods require very high signal-to-noise ratio (SNR) and/or the self-synchronization property of the chaotic system, their application to practical secure communication systems is limited. The proposed scheme in this paper uses a noise reduction method which has exhibited good performance for reducing the dynamical error. It determines which data stream comes from the particular system by comparing the power level of the dynamical error of each data stream. The advantages of the proposed system are that it requires no synchronization of the receiver to the transmitter and it is robust to channel noise.
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