Joint Photographic Experts Group (JPEG) baseline algorithm is widely used because of its high compression capability. The algorithm has a characteristic that the degradation of image quality tends to be perceived as t...
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Joint Photographic Experts Group (JPEG) baseline algorithm is widely used because of its high compression capability. The algorithm has a characteristic that the degradation of image quality tends to be perceived as the compression ratio becomes high. The eyesore degradations are false contour and mosquito. A method of improving the image quality is proposed. The first step: a domain of false contours is extracted from the image and the second step: the domain is smoothed by a fitting process. It is confirmed that this method is effective in improving the image quality degraded by the JPEG high compression. (C) 2001 Elsevier Science Inc. All rights reserved.
In this paper, we propose a Big-Gamma smoothing method for solving the P-0 matrix linear complementarity problem. We study the trajectory defined by the augmented smoothing equations and global convergence of the meth...
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In this paper, we propose a Big-Gamma smoothing method for solving the P-0 matrix linear complementarity problem. We study the trajectory defined by the augmented smoothing equations and global convergence of the method under an assumption that the original P-0 matrix linear complementarity problem has a solution. The method has been tested on the P-0 matrix linear complementarity problem with unbounded solution set. Preliminary numerical results indicate the robustness of the method.
The paper main solve above two *** the paper a Chinese Trigram model of task adaptation ability are set up.A zerogram to trigram probability statistics information base of 1994 "People Daily" are built,it ma...
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The paper main solve above two *** the paper a Chinese Trigram model of task adaptation ability are set up.A zerogram to trigram probability statistics information base of 1994 "People Daily" are built,it made use of the success experience of HMM in speech recognition, and adopted Baum-Welch algorithm for optimum of the *** weigh stands for correlation statistic reliability of these *** probability statistics matrix smooth algorithm of the parameter space was carried on,in order to offset the matrix sparse data of statistic *** "People Daily" corpus statistic results are regard as the preliminary statistic *** the changing of application domain,then the recognition accuracy rate of the preliminary statistic results are declined,we adopted "PC World" as the corpus of the changing domain and carried on successive training,then second smooth of the preliminary statistic results and successive statistic results was look on as finally results.A trigram model of task adaptation is gotten. The experiment results show,this language model the workload of successive training befits,it can effectively reduce the perplexity of language model in task changing domain,it has a high language adaptation ability in the task changing domain.
Model-based video coding has been adopted as a core experiment in ISO MPEG-4 standard. The clip-and-paste technique for putting video objects in line is an important tool to reduce the transmission rate. To assist the...
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Model-based video coding has been adopted as a core experiment in ISO MPEG-4 standard. The clip-and-paste technique for putting video objects in line is an important tool to reduce the transmission rate. To assist the clip-and-pasting method fitting into the 2-D model, we propose several smoothing algorithms for improving the quality of the reconstructed images. In this paper, the proposed smoothing algorithms can adjust deformations of zoom, tilt, and rotation object images. Luminance smoothing algorithm is also applied to compensate the light source variations. Simulation results show that the smoothing methods help to improve clip-and-paste images to achieve a satisfactory quality in visual perceptions.
Because of non-negligible ISI due to the Gaussian filter and delay spread in the GSM system, an equalizer is required. In this letter, a joint sliding window channel estimation and timing adjustment method is proposed...
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Because of non-negligible ISI due to the Gaussian filter and delay spread in the GSM system, an equalizer is required. In this letter, a joint sliding window channel estimation and timing adjustment method is proposed fur maximum likelihood sequence equalizer. And also a smoothing algorithm is presented in order to improve the equalizer performance. This smoothing scheme utilizes a variant of LMS algorithm to tune the channel coefficient estimates. Simulation results show that the proposed scheme is adequate for channel estimation of the adaptive equalizer.
VQ(Vector Quantization) reduce the bit rate by exploting the correlation in the data. To improve the performance of a compression algorithm based on VQ, this paper introduced a more efficient scanning method, i.e. Pea...
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ISBN:
(纸本)0819430064
VQ(Vector Quantization) reduce the bit rate by exploting the correlation in the data. To improve the performance of a compression algorithm based on VQ, this paper introduced a more efficient scanning method, i.e. Peanoscanning, which maintains better correlation in two dimensional data than that of raster scan, and then a hierarchical VQ based on the characteristics of image data is presented, at last we reduced the blocking effect by a smoothing algorithm.
Morphological segmentation has been proposed as an attractive alternative to transform-based compression for interframe coding of digital video. Being a spatial approach, segmentation based coding eliminates the artef...
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Morphological segmentation has been proposed as an attractive alternative to transform-based compression for interframe coding of digital video. Being a spatial approach, segmentation based coding eliminates the artefacts commonly associated with transform coding, such as ringing around sharp edges. One disadvantage of this method is that it can introduce spurious edges in the reconstructed video sequence. associated with the boundaries of the transmitted regions. The authors present a statistically derived smoothing algorithm that reduces this problem. In addition, a single-stage entropy coder for the update signal is proposed in place of the conventional two-stage algorithm. Comparisons are made between the performance of a traditional motion compensated DCT coder and segmentation based codecs (with and without smoothing) for CIF sequences at bit rates between 64 and 256 kbps. It is concluded that, at the bit rates under investigation, the segmentation based method yields improved subjective quality of the reconstructed video.
A Fortran program was developed to implement a Kalman Filter and Fixed Interval smoothing algorithm to optimally smooth data tracks generated by the short base-line tracking ranges at the Naval Torpedo Station, Keypor...
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A Fortran program was developed to implement a Kalman Filter and Fixed Interval smoothing algorithm to optimally smooth data tracks generated by the short base-line tracking ranges at the Naval Torpedo Station, Keyport, Washington. The program is designed to run on a personal computer and requires as input a data file consisting of X, Y, and Z position coordinates in sequential order. Data files containing the filtered and smoothed estimates are generated by the program. This algorithm uses a second order linear model to predict a typical target's dynamics. The program listings are in- cluded as appendices. Several runs of the program were performed using actual range data as inputs. Re- sults indicate that the program effectively reduces random noise, thus providing very- smooth target tracks which closely follow the raw data. Tracks containing data gener- ated in an overlap region where one array hands off the target to the next array are highlighted. The effects of varying the magnitude of the excitation matrix Q(k) are also explored. This program is seen as a valuable post-data analysis tool for the current tracking range data. In addition, it can easily be modified to provide improved real time, on line tracking using the Kalman Filter portion of the algorithm alone.
An adaptive smoothing method based on a least mean-square estimation is developed for noise filtering of spectroscopic data. The algorithm of this method is nonrecursive and shift-varying with the local statistics of ...
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An adaptive smoothing method based on a least mean-square estimation is developed for noise filtering of spectroscopic data. The algorithm of this method is nonrecursive and shift-varying with the local statistics of data. The mean and the variance of the observed spectrum at an individual sampled point are calculated point by point from its local mean and variance. By this method, in the resultant spectrum, the signal-to-noise ratio is maximized at any local section of the entire spectrum. Experimental results for the absorption spectrum of ammonia gas demonstrate that this method distorts less amount of signal components than the conventional smoothing method based on the polynomial curve-fitting and suppresses noise components satisfactorily. The computation time of this algorithm is rather shorter than that of the convolution algorithm with seven weighting coefficients. The a priori information for the estimation of the signal by this method are: the variance of noise, which can be attainable in the experiment; and the window function which gives the local statistics. The investigation of various types of window functions shows that the selection of the window function does not directly affect the performance of adaptive smoothing.
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