Results 141 to 150 of about 575 (174)
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Mismatched DPCM encoding of autoregressive processes
IEEE Transactions on Information Theory, 1990A method for computing the mean squared error distortion of differential pulse code modulation (DPCM) applied to Gaussian autoregressive sources is developed. This extends previous work wherein the code predictor was matched to the source. A two-dimensional version of the projection method for the computation of the stationary distribution of the joint
Morteza Naraghi-Pour, David L. Neuhoff
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Improving the rate-distortion performance of DPCM
Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings., 2003Differential pulse coded modulation (DPCM) is able to code highly correlated sources efficiently at high bit rates but not at low bit rate regions. Motivated by the rate distortion theory, a simple modified DPCM codec using multirate processing is proposed. A low-pass filter is used to limit the source signal spectrum.
Anna N. Kim, Tor A. Ramstad
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A Generalization of DPCM for Digital Image Compression
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979A natural generalization of two-dimensional digital pulsecode modulations (DPCM) has been used to handle the compression of images for human eyes only. It shows that by ignoring the mean-square error (MSE) and wisely arranging the errors in the right place, a simple method can achieve very good results.
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Two‐dimensional interpolative DPCM
Electronics and Communications in Japan (Part I: Communications), 1988AbstractDifferential PCM (DPCM) has often been used for encoding of images, but its efficiency is very poor at low transmission rates. Discussion of DPCM is based on an autoregressive (AR) model which is causal in the case of raster scan sampling. However, originally, images do not satisfy causality in this sense, and a better description of the two ...
Shiro Handa, Hatsukazu Tanaka
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Generalised locally adaptive DPCM
Proceedings DCC '97. Data Compression Conference, 1997Summary form only given. In differential pulse code modulation (DPCM) we make a prediction f/spl circ/=/spl Sigma/a(i)-f(i) of the next pixel using a linear combination of neighbouring pixels f(i). It is possible to have the coefficients a(i)s constant over a whole image, but better results can be obtained by adapting the a(i)s to the local image ...
T. Seemann, P. Tischer
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Stability of the DPCM transmission system
IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1992Bounded input-bounded output stability of the differential pulse code modulation (DPCM) transmission system is investigated. The output is calculated by a nonlinear feedback loop. In the feedforward path the quantizer characteristic can be taken as continuous. It exhibits a threshold and has a linear part with a variable slope p greater than 1.
Macchi, Odile, Uhl, Christine
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Improving DPCM system performance
IEEE Global Telecommunications Conference, 1989, and Exhibition. 'Communications Technology for the 1990s and Beyond, 2003A differential pulse code modulation (DPCM) system provides a fast and inexpensive data compression technique for analog signals. Two methods of improving the performance of DPCM systems are studied: the introduction of delays using incremental tree coding techniques and the design of nonuniform quantizers based upon optimization theory.
J.G. Dunham, A. Ghosh
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International Conference on Acoustics, Speech, and Signal Processing, 2002
The stability of the classical differential pulse code modulation (DPCM) transmission systems is considered in the sense of having a bounded prediction error e=s-s for a bounded input s. The difficulty stems from the nonlinear and recursive nature of the predictor, due to the inclusion of quantization in the filtering loop that achieves prediction. The
Christine Uhl, Odile Macchi
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The stability of the classical differential pulse code modulation (DPCM) transmission systems is considered in the sense of having a bounded prediction error e=s-s for a bounded input s. The difficulty stems from the nonlinear and recursive nature of the predictor, due to the inclusion of quantization in the filtering loop that achieves prediction. The
Christine Uhl, Odile Macchi
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A DPCM system with modulo limiters
IEEE Global Telecommunications Conference and Exhibition. Communications for the Information Age, 2003The authors introduce a DPCM (differential pulse code modulation) system with modulo limiting (DPCM-ML). The ML in the DPCM system compresses the dynamic range of the prediction error by 6 dB. Therefore, fewer quantization levels are required to maintain the same level of quantization noise as in DPCM without ML.
C.H. Lu, A.A. Acampora
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DPCM Picture Coding with Adaptive Prediction
IEEE Transactions on Communications, 1977Adaptive prediction is a method of improving the prediction in differential pulse-code modulation (DPCM) systems. The information on contour directions derived from neighboring picture elements is used to select a suitable prediction value for the actual sample.
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