Backward Adaptive Prediction Research Articles

무손실 영상 압축을 위한 변형된 정수 변환 계수에 대한 순방향 적응 예측 기법

This paper proposes a compression scheme based on the modified reversible integer transform (MRIT) and forward adaptive prediction for lossless image compression. JPEG XR is the newest image coding standard with high compression ratio and that composed of the Photo Core Transform (PCT) and backward adaptive prediction. To improve the efficiency and quality of compression, we substitutes the PCT and backward adaptive prediction for the modified reversible integer transform (MRIT) and forward adaptive prediction, respectively. Experimental results indicate that the proposed method are superior to the previous method of JPEG XR in terms of lossless compression efficiency and computational complexity.

A PREDICTIVE CODING METHOD FOR LOSSLESS COMPRESSION OF IMAGES

Images are an important part of today's digital world. However, due to the large quantity of data needed to represent modern imagery the storage of such data can be expensive. Thus, work on efficient image storage (image compression) has the potential to reduce storage costs and enable new applications.This lossless image compression has uses in medical, scientific and professional video processing applications.Compression is a process, in which given size of data is compressed to a smaller size. Storing and sending images to its original form can present a problem in terms of storage space and transmission speed.Compression is efficient for storing and transmission purpose.In this paper we described a new lossless adaptive prediction based algorithm for continuous tone images. In continuous tone images spatial redundancy exists.Our approach is to develop a new backward adaptive prediction techniques to reduce spatial redundancy in a image.The new prediction technique known as Modifed Gradient Adjusted Predictor (MGAP) is developed. MGAP is based on the prediction method used in Context based Adaptive Lossless Image Coding (CALIC). An adaptive selection method which selects the predictor in a slope bin in terms of minimum entropy improves the compression performance.

Speech coding based on adaptive mel‐cepstral analysis and its evaluation

AbstractThis paper proposes the ADPCM speech coding system using mel‐cepstrum as the parameter for the short‐term prediction. In the proposed coding system, the backward type adaptive prediction is applied based on the adaptive mel‐cepstrum analysis. Operations such as noise shaping and postifitering are executed through the melcepstrum. Consequently, it is expected that the noise shaping and the postfiltering have the effect which is matched to the human auditory characteristics.This paper presents the configuration of the coding system with some improvements such as the addition of the pitch predictor, and the quality of the coded speech is evaluated. It is shown as a result that the proposed coding system realizes the same speech quality at 16 kbit/s as that of the 32‐kbit/s ADPCM, even though there is no algorithm delay.

Robust backward adaptive pitch prediction forspeech coder

To improve the error performance of a speech coder, a smoothing method for the backward adapted pitch preditor is proposed. The smoother with three taps can have fixed coefficients or variable coefficients depending on the estimated autocorrelation function of the pitch synthesiser output. The inclusion of a variable smoother can reduce the effect of channel errors and track the pitch period change within a block.

The UK candidate 16 kbit/s speech codec for the GSM Pan-European study on digital cellular land mobile radio

A 16 kbit/s speech codec is described which was developed by British Telecom Research Laboratories and selected as the UK candidate to the GSM Pan-European study on digital cellular land mobile radio. The hardware described and test results presented correspond to the equipment tested in the European contest at Turin, Italy. The codec, whilst giving good speech quality, also offers several important features including low delay, low computational complexity and a good tolerance to transmission errors. The codec employs an 8-band subband coding algorithm incorporating backward-adaptive quantisation and backward-adaptive prediction. The hardware implementation described uses a pair of digital signal processing devices, thereby giving a very compact realisation. The results of both subjective and objective tests are also presented.

Subband coding with adaptive prediction for 56 kbits/s audio

This paper reports on a continuation of previous work on the digital coding of 7 kHz wide-band audio at 56 kbits/s [1]. Focus in the present paper is on 5-band subband coding (SBC). Specifically, we consider SBC with adaptive PCM coding in each subband (SBC-APCM); DPCM with backward adaptive prediction (ADPCM); and, most importantly, the combination of the two techniques, SBC-ADPCM. The main conclusion of this paper is that SBC-ADPCM, with a fourth-order backward adaptive predictor in each subband, has a much better objective performance than SBC-APCM for both speech and music inputs, with segmental signal-to-noise ratio gains in the order of 6-8 dB. Informal listening tests confirm that these SNR gains are accompanied by gains in subjective quality. While SNR gains were no higher with two eighth-order predictors that were carefully optimized, small perceptual gains were noticeable with certain inputs. In the absence of transmission errors, there was very little difference between the performance of an 8-pole predictor and a 2-pole 6-zero predictor. In the full-band ADPCM coder, however, the 8-pole predictor was significantly better in the zero-error case.

Backward adaptive prediction as spectral analysis within a closed loop

Backward adaptive prediction in differential pulse code modulation (DPCM) systems is represented as a problem of spectral analysis within a closed loop. Using this spectral analysis approach, the backward adaptive all-pole predictor in classic DPCM is shown to perform well, given good initial conditions and a slowly varying DPCM system input. However, when it loses track, the all-pole predictor is shown to have a tendency to track itself rather than changes in the input signal transfer function. The use of a pole-zero predictor improves the situation since the backward adaptation of the zeros is clearly dependent upon the input signal transfer function and thus should respond to changes or nonstationarities in the DPCM system input. The backward adaptation of the poles in the pole-zero predictor is able to track changes in the system input through variations in the predictor zeros. The results provide additional motivation for including zeros in backward adaptive predictors for DPCM.

Multilingual comparison of forward and backward adaptive prediction in DPCM

Results of experimental comparisons of forward- and backward-adaptive prediction in differential pulse code modulation (DPCM) of speech are presented. Two different types of comparisons are conducted. In one comparison, both predictors are used with the same three/five-level pitch compensating quantizer (PCQ). For this comparison, forward prediction clearly outperforms backward prediction, but with the penalty of a 10% increase in data rate due to the need to transmit coefficients. In the second comparison, the forward-prediction DPCM system and the backward-prediction DPCM system are constrained to have the same data rate of 16 kbits/sec. The backward-adaptive predictor outperforms forward prediction for this latter comparison. The speech data base for the simulations is one sentence spoken by a male speaker in four different languages: English, French, German, and Arabic. The performance comparisons are based on signal-to-quantization noise ratio, signal-to-prediction error ratio, sound spectrograms, and formal subjective listening tests.

Kalman Backward Adaptive Predictor Coefficient Identification in ADPCM with PCQ

Kalman backward adaptive predictor coefficient identification is combined with a modified pitch-compensating quantizer (MPCQ) to produce a high-performance adaptive differential pulse code modulation (ADPCM) system for operation at data rates of 12-16 kbits/s. The Kalman/MPCQ system is compared to an ADPCM system using a Kalman algorithm and robust Jayant qnantization and to a system with a fixed-tap predictor and MPCQ. The performance indicators are signal-to-quantization noise ratio (SNR), sound spectrogram analyses, and formal subjective listening tests. The SNR comparisons indicate that the Kalman/ MPCQ system has the highest SNR, followed by the fixed-tap/MPCQ system, and then the Kalman/robust Jayant system. Subjective listening test results show that the Kalman/MPCQ system is preferred over the fixed-tap/MPCQ system 100 percent of the time and over the Kalman/ robust Jayant system 80 percent of the time. Kalman adaptation thus provides an important perceptual effect not evident in the SNR's. The previously catastrophic effects of transmission errors on backward adaptive prediction are eliminated by simple ADPCM system modifications that do not affect the SNR or subjective quality of the output in the absence of errors for the five sentences studied. The problem of tandeming with a linear predictive coder (LPC) is investigated by using LPC processed speech as input to the three ADPCM systems and by using the output of the three ADPCM systems as input to an LPC analysis algorithm. For the LPC to ADPCM connection, the two systems with the MPCQ produce good quality output speech, while the system with robust Jayant quantization exhibits a fading phenomenon. For the ADPCM into LPC analysis, all three systems produce speech of approximately the same quality, with the fixedtap system being slightly, noisier. Using a distance measure proposed by Itakura, the predictor coefficients computed from the three ADPCM system outputs are compared with the predictor coefficients calculated from the uncontaminated speech. According to this distance measure, the coefficients computed from the Kalman/MPCQ system output are much closer to the desired coefficients than are those computed by the other two systems.

Adaptive prediction in speech differential encoding systems

The design of speech coders that produce high-quality highly intelligible speech at 6 to 16 kb/s while retaining robustness to background and transmission impairments is an area of current research interest. Differential encoding structures employing adaptive quantization and adaptive prediction constitute one of the most promising approaches to achieving these design objectives. This paper focuses on the design and analysis of adaptive predictors for differential encoders. Several differential encoding systems, including adaptive predictive coding, differential pulse-code modulation, noise feedback coding, direct feedback coding, and prediction error coding, are described and related. Adaptive quantizers are briefly discussed and quantitative and qualitative indicators of speech coder performance are defined. The channel model, the speech model, and the research problem statements used in the design of differential encoders and adaptive predictors are presented. The nomenclature and theory of forward and backward adaptive prediction are developed, and several new backward adaptive algorithms based on various assumptions are presented. A detailed survey of theoretical and simulation results on adaptive prediction for speech differential encoders is given, and the effects of background and transmission impairments on these systems are discussed, Finally, the impact of adaptive predictors on rate distortion theory motivated coders is indicated. Numerous areas for future research are highlighted.

Topics on speech waveform coding activities in Japan

Topics on ADPCM and ADM technique developments in Japan are described. First, an ADPCM code sequence optimization method by K. Fushikida is discussed for an ADPCM with an adaptive quantization and fixed predictor. The method uses a technique reminiscent of dynamic programming and optimizes code sequence. It is shown that about 2‐dB SNR improvement is obtainable for speech at 32 kbps (4 bits/sample). Second, another ADPCM technique by T. Araseki and K. Ochiai is described. This technique is suitable for use at the bit rate less than 32 kbps. Two adaptive predictors connected in a cascaded form are used. One of the predictors has an ordinary small number of prediction taps. However, the other predictor possesses a considerably large number of predictor taps which are used to predict speech waveform in one pitch period apart. A backward adaptive prediction technique with a gradient method is used for each of the two adaptive predictors. Finally, performance improvement techniques and LSI implementation by A. Tomozawa and K. Niwa are described for a discretely variable slope 32 kbps ADM (DVSD).