Conventional Differential Pulse Code Modulation Research Articles

A prequantizer with the human visual effect for the DPCM

Abstract In this paper, a new differential pulse code modulation (DPCM) structure is proposed to improve the conventional DPCM. In the conventional DPCM, the design of the prediction error quantizer is mainly a nonuniform optimum quantizer. This kind of the optimum quantizer must require some statistical data in advance such that the complexity of the entire system increases. In this paper, the proposed DPCM uses a prequantizer to prequantize image data instead of an optimum quantizer to quantize the prediction error. The prequantizer only requires the mean of the image as a parameter to adapt the quantizer. In addition, the quantizer also matches the human visual effect, the Weber's Law. The prequantizer increases the correlation between pixels largely such that the predictor can predict the next pixel more accurately. It reduces the entropy and bit-rate of the prediction error largely. The simulation indicates the bit-rate with the proposed method is 1 bit per pixel less than that with the conventional DPCM under the same image quality. The proposed method also compares with the block truncation coding (BTC). Under the same bit-rate, the image quality with the proposed method is 10 dB better than that with the BTC method. In addition, the computation complexity of the proposed method is not greater than that of the conventional DPCM or BTC.

Interframe DPCM with robust median-based predictors for transmission of image sequences over noisy channels

A new image sequence coding technique based on robust median-based predictors is presented for the transmission of image sequences over noisy channels. We analyze the robustness of median-based predictors against channel errors. A heuristic algorithm for the design of a robust predictor from a given median-based predictor is presented. It is shown that with small modifications in terms of a necessary requirement for a median-based predictor to be robust against channel errors, the robustness of a given median-based predictor can be considerably improved. Simulations on a real image sequence show significant improvement over the conventional differential pulse code modulation (DPCM) at high bit error rate (BER) using this new technique. The technique does not increase the transmission rate. It is shown that the quality of reconstructed images obtained by robust median-based predictors can be further improved by postprocessing the image using a nonlinear detail-preserving noise-smoothing filter.

The Effect of Channel Coding on the Efficiency of Cellular Mobile Radio Systems

Error correcting codes have two opposite effects on the efficiency of cellular mobile-radio systems. Although they increase the bandwidth per channel, the codes also make signals more robust and thereby reduce the required distance between users of the same frequency band. This paper reports a mathematical study of the interactions of these two effects in determining the efficiencies of a large number of sourcecode and channel-code combinations. Within a statistical performance objective (baseband SNR \geq 11 dB for 90 percent of the users), the most efficient scheme in this study has an embedded differential pulse code modulation (DPCM) source code and a rate 1/2 channel code that protects 2 bits of each 4 bit DPCM code word. Based on a conservative model of cellular transmission, we estimate that the bandwidth efficiency is 3 users/cell/MHz of system bandwidth. By contrast, there are only 1.2 users/cell/MHz with uncoded transmission and 4.5 users/cell/MHz with a rather complicated variable-rate scheme. We also observe that the embedded source code, originally devised for variable-rate operation, has a higher baseband SNR than conventional DPCM in certain fixed-rate environments.

Transmission Errors and Forward Error Correction in Embedded Differential Pulse Code Modulation

We have derived formulas for the combined effects of quantization and transmission errors on the performance of embedded Differential Pulse Code Modulation (DPCM), a source code that can be used for variable-bit-rate speech transmission. Our analysis is more general and more precise than previous work on transmission errors in digital communication of analog signals. Special cases include conventional DPCM and Pulse Code Modulation (PCM). Our main result is a signal-to-noise ratio formula in which the effects of source characteristics (input signal, codec design parameters) and the effects of transmission characteristics (modulation, channel, forward error correction) are clearly distinguishable. We also present, in computationally convenient forms, specialized formulas that apply to uncoded transmission through a random-error channel, transmission through a slowly fading channel, and transmission with part or all of the DPCM signal protected by an error-correcting code. Numerical results show how channel coding can have different effects on conventional and embedded DPCM. They also show how the binary-number representation of quantizer outputs influences performance.