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We present an in-depth analysis of the problem of lossy compression of binary sources in the presence of correlated side information, where the correlation is given by a generic binary asymmetric channel and the Hamming distance is the distortion metric. Our analysis is motivated by systematic rate-distortion gains observed when applying asymmetric correlation models in Wyner-Ziv video coding. Firstly, we derive for the first time the rate-distortion function for conventional predictive coding in the binary-asymmetric-correlation-channel scenario. Secondly, we propose a new bound for the case where the side information is only available at the decoder - Wyner-Ziv coding. We conjecture this bound to be tight. We show that the maximum rate needed to encode as well as the maximum rate-loss of Wyner-Ziv coding relative to predictive coding correspond to uniform sources and symmetric correlations. Importantly, we show that the upper bound on the rate-loss established by Zamir is not tight and that the maximum value is actually significantly lower. Moreover, we prove that the only binary correlation channel that incurs no rate-loss for Wyner-Ziv coding compared to predictive coding is the Z-channel. Finally, we complement our analysis with new compression performance results obtained with our state-of-the-art Wyner-Ziv video coding system.

A new coding scheme for image transmission over noisy channel is proposed. Similar to standard image compression, the scheme includes a linear transform followed by successive refinement scalar quantization. Unlike conventional schemes, in the proposed system the quantized transform coefficients are linearly mapped into channel symbols using systematic linear encoders. This fixed-to-fixed length "linear index coding" approach avoids the use of an explicit entropy coding stage (e.g., arithmetic or Huffman coding), which is typically fragile to channel post-decoding residual errors. We use linear codes over GF(4), which are particularly suited for this application, since they are matched to the dead-zone quantizer symbol alphabet and to the QPSK modulation used on the deep-space communication channel. We optimize the proposed system where the linear codes are systematic Raptor codes over GF(4). The rateless property of Raptor encoders allows to achieve a "continuum" of coding rates, in order to accurately match the channel coding rate to the transmission channel capacity and to the quantized source entropy rate for each transform subband and refinement level. Comparisons are provided with respect to the concatenation of state-of-the-art image coding and channel coding schemes used by Jet Propulsion Laboratories (JPL) for the Mars Exploration Rover (MER) Mission., 36 pages, 5 figures, to be submitted to IEEE Trans. on Communications

Block-coded modulation with interblock memory (BCMIM) is a variation of block-coded modulation (BCM) which is designed for multilevel coding. By providing interblock memory between adjacent blocks, the coding rate of a BCMIM scheme can be increased without decreasing the minimum squared Euclidean distance (MSED) as compared to the original BCM. In an early version of BCMIM, interblock coding is provided only between the first two coding levels of adjacent blocks. In this paper, we design BCMIM with a more general form for which interblock coding can be introduced among many coding levels. In this way, we can further increase the coding rate of BCMIM without decreasing the MSED. We provide many examples to show the advantages of BCMIM with the general form. Most of the examples are designed based on multidimensional signal sets, since a multidimensional signal set can provide more coding levels than a two-dimensional (2-D) signal set.

Subband coding with vector quantization is addressed in this paper. Forming the data vectors from both between and within the subbands is considered. The former of these two schemes is referred to as interband coding and the latter as intraband coding. Interband coder design is relatively straightforward since the design of the single codebook involved follows readily from a representative set of interband data vectors. Intraband coder design is more complicated since it entails the selection of a vector dimension and a bit-rate for each subband. The main contribution of this work is an optimal methodology for intraband subband vector quantizer design. The problem formulation includes constraints on the bit-rate and the encoding complexity and is solved with nonlinear programming methods. Subband vector quantization image coding in conjunction with a human visual system model is thoroughly investigated. Results of a large number of experiments indicate that the optimal intraband coder yields superior results from quantitative as well as subjective points of view than the interband coder for comparable bit-rates. This improvement becomes more pronounced as the computational complexity of the intraband encoder is allowed to increase. >

This paper presents a transform coding algorithm devoted to high quality audio coding at a bit rate of 64 kbps per monophonic channel. It enables the transmission of a high quality stereo sound through the basic access (2B channels) of ISDN. Although a complete system including framing, synchronization and error correction has been developed, only the bit rate compression algorithm is described here. A detailed analysis of the signal processing techniques such as the time/frequency transformation, the pre-echo reduction by adaptive filtering, the fast algorithm computations, etc., is provided. The use of psychoacoustical properties is also precisely reported. Finally, some subjective evaluation results and one real time implementation of the coder using the ATT DSP32C digital signal processor are presented. >

A new approach to image sequence coding based on variable-rate entropy-constrained subband coding (ECSBC) is described. The corresponding practical implementation of the ECSBC scheme for fixed-rate channels is developed by extending recent adaptive entropy-coded (AEC) quantization techniques. Although the entropy-constrained design of subband coding systems provides improve coding efficiency compared to level-constrained design approaches, the resulting coding system generates variable-rate outputs which must be buffered before fixed-rate transmissions. In this case, the finite buffer, however large, that interfaces the encoder and the channel will eventually overflow or underflow, resulting in a catastrophic loss of encoder-decoder synchronism with an associated large amount of distortion. A buffer-adaptive arithmetic-coded implementation of the ECSBC scheme, called adaptive entropy-coded subband coding (ECSBC/AEC), is described to completely eliminate the associated encoder buffer overflow/underflow problems, even with a very small encoder buffer. >

Protection of images that are encoded using subband coding from channel error is addressed. In this scheme the low-pass subband is encoded using DPCM (differential pulse-code modulation), and the other subbands are encoded using a scalar quantizer. The quantizers are all Lloyd-Max quantizers, from which the representation levels have fixed length codewords. First, considering only single errors in each codeword, a channel error distortion measure is derived for each quantizer, that is, for each subband. Codewords are assigned to the quantizer representation levels, yielding a low value of the distortion measure. Next, sets S/sub ij/ consisting of the jth bit from subband i are formed. Each set S/sub ij/ is assigned a particular BCH code C/sub ij/. An algorithm that optimally assigns BCH codes C/sub ij/ to each set S/sub ij/, based on a channel error distortion measure for the entire image, is derived. The protection scheme is adaptive, because each set of bits within each subband can be assigned a different error protection code. Examples show that this approach is preferable to assigning equal error protection codes to each set of bits. It is shown that in the case of a channel error probability of 10/sup -3/, only 5% to 10% extra bits are needed for adequate channel error protection. >

A common theory of lapped orthogonal transforms (LOTs) and critically sampled filter banks, called L into N coding (LINC), is presented. The theory includes a unified analysis of both coding methods and identity relations between the transform, inverse transform, analysis filter bank, and synthesis filter bank. A design procedure for LINC analysis/synthesis systems, which satisfy the conditions for perfect reconstruction, is developed. The common LINC theory is used to define an ideal LINC system which is used, together with the power spectral density of the input signal, to calculate theoretical bounds for the coding gain. A generalized overlapping block transform (OBT) with time domain aliasing cancellation (TDAC) is used to approximate the ideal LINC. A generalization of the OBT includes multiple block overlap and additional windowing. A recursive design procedure for windows of arbitrary lengths is presented. The coding gain of the generalized OBT is higher than that of the Karhunen-Loeve transform (KLT) and close to the theoretical bounds for LINC. In the case of image coding, the generalized OBT reduces the blocking effects when compared with the DCT. >

In many source and data compression schemes, information relating to positions of high-energy samples or areas of importance often needs to be relayed to the decoder. The error resilient positional code (ERPC) is an efficient fixed-rate coding scheme for encoding such positional information, or, equivalently, sparse binary data patterns. It has also been designed with good channel error robustness properties, such that the decoded data quality degrades gracefully with worsening channel conditions, without the possibility of catastrophic breakdown or loss of sync. In this work, the coding efficiency of the ERPC is compared to a few other standard schemes. It is found to be efficient and its error extension in terms of the expected number of samples corrupted per bit error is reported and shown to be low and noncatastrophic. The ERPC is applied to an image coding example based on subband coding and vector quantization. It results in an efficient adaptive codec capable of operating in harsh channel conditions, without the aid of error correction or detection techniques. >

The need for a 16-kb/s speech coding algorithm that has very low coding delay while achieving essentially the same high quality as the 32-kb/s adaptive differential pulse code modulation (ADPCM) standard G.721 is addressed. The authors describe low-delay vector excitation coding (LD-VXC), a new coding algorithm which provides high quality with less than 2 ms of coding delay and is robust to transmission errors. The algorithm combines techniques such as vector quantization, analysis-by-synthesis, and perceptual weighting together with backward adaptive linear predictive encoding, and uses a novel long-term predictor employing backward adaptive pitch tracking. Perceptually based nose shaping and postfiltering contribute to the masking of audible quantization noise. >

A picture data compression method consisting of a hybrid cascade having four processing stages is presented. The processing stages are: predictive ordering technique (POT), feedback transform coding (FTC), vertical subtraction of quantized coefficients (VSQC), and predictive coding refinements in the signal space consisting of either overshoot suppression (OS) as a first variant or hybrid block truncation coding (HBTC) as a second one. Each of these stages is described, and reconstructed pictures are presented with their coding fidelity performances (mean square quantization error, mean absolute error and signal-to-noise ratio), using as test pictures a portrait and a LANDSAT image. It is shown that good quality images at low bit rates (0.55 to 1.1 bits/pixel) have been obtained. >

A motion compensated interframe subband coding algorithm suitable for a wide range of video coding applications is described. In this approach the spectrum of each frame of video signal is first decomposed into smaller frequency bands where each can then be coded accordingly. For the best performance a combination of hybrid DCT/DPCM (discrete cosine transform/differential pulse code modulation), interframe DPCM, and intraframe PCM was considered. To preserve its hierarchical structure each band is coded independently of higher frequency bands but can share information with the lower bands. A simulation was carried out for HDTV sequences. >

A model of multiuser variable rate subband coding of speech incorporating digital speech interpolation (DSI) is presented and analyzed. A dynamic bit assignment algorithm which minimizes the mean squared reconstruction error is presented. A backward estimation of subband variances which makes the bit assignment algorithm backward-adaptive and greatly reduces the need to send side information is proposed. A novel switched-stepsize adaptation algorithm is used at the coders to improve system performance. With adaptive buffer control, buffer overflow is completely prevented. It has been shown by simulation means that a 2:1 DSI gain can be obtained with a relatively small buffer size. >

Two-dimensional transform coding and hybrid transform/DPCM coding techniques have been investigated extensively for image coding. This paper presents a theoretical and experimental extension of these techniques to the coding of sequences of correlated image frames. Two coding methods are analyzed: three-dimensional cosine transform coding, and two-dimensional cosine transform coding within an image frame combined with DPCM coding between frames. Theoretical performance estimates are developed for the coding of Markovian image sources. Simulation results are presented for transmission over error-free and binary symmetric channels.

Visibility functions measure the relative visibility of noise added to a picture at those points where some measure of local activity exceeds a given threshold. The functions are obtained from a series of subjective experiments and vary with the content of the picture. Visibility functions have been used to design quantizing characteristics for DPCM coding of monochrome and color signals and for three-dimensional transform coding. We consider an alternative approach to determining the visibility function that obviates the need for repeated picture-dependent subjective tests. The visibility function is assumed to consist of two parts, a picture-dependent component and viewer-dependent component (referred to as the masking function). The visibility function may be approximated by the quotient of a probability density function raised to a power and the masking function. The role of probability is found to be weaker where the viewer has more opportunity to scrutinize the picture.

This paper describes the results of theoretical studies made on performance of various kinds of intrafield two-dimensional transform codings (Hadamard, cosine, and slant) for carrier chrominance signals, by introducing a new measure (transform coefficients of zero variance) for such coding performances. In addition, a comparative study of the performance of these transform codings is performed for different sampling frequencies (2f_{sc}, 3f_{sc}, 4f_{sc}) with the same transmission rate, taking into account the tradeoff between the number of bits assigned to a picture element at each sampling frequency and the autocorrelation between adjacent picture elements.

A two-dimensional, 32nd-order orthogonal transform coding system which performs three types of transformations in realtime for NTSC color television signals has been developed. This paper reports on a hardware realization of this system, the optimum bitassignments for 32 and 22 Mbit/s transmission rates and the effects of bit errors during transmission. Through the evaluation of picture quality, the system gave a fine quality of pictures after compressing an 8-bit digitized television signal into 3 bits/pel corresponding to 32 Mbit/s transmission, and a passable quality of pictures by 2.25 bits/ pel corresponding to 22 Mbit/s transmission.

This paper reviews our recent efforts in the design and implementation of real-time speech coders. We discuss our approach and methodology for real-time hardware for coder techniques ranging from low to high complexity. Examples of realizations are given for each approach. They include adaptive differential PCM coding, subband coding, harmonic scaling with subband coding, and adaptive transform coding. Low to medium complexity techniques are based on the use of the Bell Laboratories digital signal processing (DSP) integrated circuit. High complexity block processing techniques are based on the use of an array processing computer. We conclude with an assessment of the performance versus complexity tradeoffs involved in these coding methods.

Adaptive vector transform quantization (AVTQ) as a coding system is discussed. The optimal bit assignment is derived based on vector quantization asymptotic theory for different PDFs (probability density functions) of the transform coefficients. Strategies for shaping the quantization noise spectrum and for adapting the bit assignment to the changes in the speech statistics are discussed. A good estimate of the efficiency of any coding system is given by the system coding gain over scalar PCM (pulse code modulation). Based on the optimal bit allocation, the coding gain of the vector transform quantization (VTQ) system operating on a stationary input signal is derived. The VTQ coding gain demonstrates a significant advantage of vector quantization over scalar quantization within the framework of transform coding. System simulation results are presented for a first-order Gauss-Markov process and for typical speech waveforms. The results of fixed and adaptive systems are compared for speech input. Also, the AVTQ results are compared to known scalar speech coding systems. >

This paper presents the coding algorithms and simulation results of multimode movement-compensated interframe video coders operating at 15 and 20 mbits/s for broadcast applications. The coding algorithms are based on a motion-compensated predictive coding approach. Simulation results using samples of broadcast video sequence indicate that excellent picture quality is obtained at the 20 Mbit/s transmission bit rate. Results of informal subjective evaluation of picture quality are also presented.

Since differential-pulse-code modulation (DPCM) and orthogonal transform coding (OTC) are the most fundamental methods of high-efficiency coding (bit-reduction method), it is important to clarify the basic coding characteristics of these methods and the difference between them in order to utilize the bit-reduction method effectively. This paper theoretically as well as experimentally compares the coding efficiency of a DPCM having a two-dimensional predictor with that of a two-dimensional Hadamard transform coding method (HTC) in the intrafield coding of the NTSC composite signal. The comparison evidenced that the distinctive difference in coding characteristics between DPCM and HTC depends greatly on the power level of carrier chrominance signals. That is, it is confirmed theoretically and experimentally that the coding efficiency of the HTC is far lower than that of the DPCM in the case of a signal having a high power level carrier chrominance signal such as a color-bar signal.

This paper describes novel adaptation strategy for hybrid transform/DPCM image coders. This strategy has yielded a 2-8 dB increase in signal-to-noise ratio in the transmission of a head and shoulders image at bit rates of 1-4 bits per pel and one-dimensional transform block sizes of 2-16.

In this paper we source encode the truncated block used in block truncation coding. It is shown that the truncated block is well approximated by wide-sense Markoff statistics; a signal having these characteristics has a high probability of belonging to the root signal set of median filters. Because the root signal space is much smaller than the binary space, it takes fewer bits to specify the truncated block in the root signal space, obtaining in this manner rate compression. Using two-dimensional filtering we can reduce the standard BTC rate of 1.63 bits/pel to 1.31 bits/pel. Using one-dimensional filtering along with a trellis encoder, rates close to 1.1 bits/pel are obtained with this fixed-length coding method.

This paper describes a transform image coding system that uses soft decision demodulation to control channel errors. In soft decision demodulation, if certain received bits of a codeword representing a coefficient are unreliable, then the codeword is rejected and the corresponding coefficient is replaced with an estimate. By monitoring the three highest energy DCT coefficients, the reconstructed image quality can be improved for a channel with a bit error probability of 10-2.

This paper reviews the field of the efficient coding of color television signals. Because this paper is perhaps the first review on this topic, some background is given in the areas of colorimetry, visual perception of color and color television systems. We assume that the reader has some familiarity with luminance encoding techniques. Coding techniques themselves are divided into two broad groups: component coding methods in which each component (usually three) is coded separately, and composite coding methods in which the composite television signal with its "color" modulated subcarrier is processed as a single entity. Both approaches are covered in detail. The field is still growing, pushed primarily by the desire in the television area to find digital coding standards accepted by both broadcasters and carriers and suitable for use with NTSC, PAL and SECAM television systems. We discuss this aspect by comparing composite and component coding methods.

A method is presented to automatically inspect the block boundaries of a reconstructed two-dimensional transform coded image, to locate blocks which are most likely to contain errors, to approximate the size and type of error in the block, and to eliminate this estimated error from the picture. This method uses redundancy in the source data to provide channel error correction. No additional channel error protection bits or changes to the transmitter are required. It can be used when channel errors are unexpected prior to reception.

A theoretical method of evaluating degradations of variable rate coders in a multichannel digital speech interpolation (DSI) system is developed. Each of the coder outputs has a variable rate based on the algorithm. The DSI system multiplexes the outputs of these variable rate coders into a fixed bit rate channel. During periods of high activity all active users are served, but at a reduced rate depending on the demand. The degradation due to high activity is shared by all active users. This system avoids speech clipping and "freeze-out" distortion. Theoretical expressions of the system overload probability and the probability of degradation to a particular user in the DSI system are derived. Two types of variable rate coders, namely, a constant quality subband coder and a constant noise subband coder, are chosen and used as examples. Comparisons of the degradations are made between the theoretical results and computer simulated results for the two types of variable rate coders, and close agreement is observed. The theory is applicable to other variable rate coding algorithms as well. In this study, all of the simulations are made at 40 percent speech activity and the average rate of the variable rate coders is close to 16 kbits/s. Objective quality measures indicate that in a system with a trunk size larger than 40, the variable rate coder DSI system can achieve a 2:1 compression with a degradation of less than 1 dB compared to non-DSI variable rate coders. This corresponds to a total gain of 8:1 when compared to 64 kbit/s PCM.

This paper deals with the application of multipath search coding (MSC) concepts to the coding of stationary memoryless and correlated sources and of speech signals at a rate of one bit per sample. We have made use of three MSC classes: 1) codebook coding (vector quantization), 2) tree coding, and 3) trellis coding. This paper explains the performances of these coders and compares them both with those of conventional coders and with rate-distortion bounds. Figs. 2 and 3 demonstrate the potentials of MSC coding strategies. The paper reports also on results of MSC coding of speech, where both the strategy of adaptive quantization and of adaptive prediction were included in coder design.

Chain coding technique, originally developed for digital representation and processing of line drawing data, has been implemented in a transform image coding algorithm with significant performance improvement. The algorithm is based on the observation that the boundary of the regions of zero coefficients within a transform block can be efficiently represented by sequences of fixed line segments (chains). Preliminary results indicate significant improvements over the basic coder algorithm in which the consecutive zeros in the transform block were runlength coded. The additional implementation complexity is modest.

In interframe coding the content of the frame memory can also be utilized for the prediction of the luminances of moving area picture elements (pels), provided that their displacement has been measured and transmitted. After an analysis of methods for the optimal segmentation of the image into areas corresponding to background, translating objects, and areas not predictable from the previous frame, experimental results of the coding are given; it can be seen that the bit rates are about halved with respect to plain interframe coding.

A novel two-dimensional subband coding technique is presented that can be applied to images as well as speech. A frequency-band decomposition of the image is carried out by means of 2D separable quadrature mirror filters, which split the image spectrum into 16 equal-rate subbands. These 16 parallel subband signals are regarded as a 16-dimensional vector source and coded as such using vector quantization. In the asymptotic case of high bit rates, a theoretical analysis yields that a lower bound to the gain is attainable by choosing this approach over scalar quantization of each subband with an optimal bit allocation. It is shown that vector quantization in this scheme has several advantages over coding the subbands separately. Experimental results are given, and it is shown the scheme has a performance that is comparable to that of more complex coding techniques. >

Since DPCM and transform coding are two fundamental approaches to high-efficiency (bit reduction) coding, it is important to clarify the basic coding characteristics of these approaches and the differences between them in order to utilize the high-efficiency coding method effectively. It is important to compare them not only from the standpoint of coding performance as optimized coding schemes based on the statistics of the input picture signal, but also from that of the robustness of coding performance for the variation of picture statistics to be coded. This paper theoretically compares the robustness of the coding performance of DPCM having a two-dimensional predictor with that of a two-dimensional Hadamard transform coding in an intrafield coding method of the NTSC composite signal. The comparison provides theoretical evidence that transform coding is more stable than DPCM, and this tendency is marked at lower bit rates such as 1 or 2 bits/pel, while DPCM has a higher coding performance for pictures with high autocorrelation.

Two hybrid coding systems utilizing a cascade of a unitary transformation and differential pulse code modulators (DPCM) systems are proposed. Both systems encode the transformed data by a bank of DPCM systems. The first system uses a one-dimensional transform of the data where the second one employs two-dimensional transformations. Theoretical results for Markov data and experimental results for a typical picture are presented for Hadamard, Fourier, cosine, slant, and the KarhunenLoeve transformations. The visual effects of channel error and also the impact of noisy channel on the performance of the hybrid system, measured in terms of the signal-to-noise ratio of the encoder, is examined and the performance of this system is compared to the performances of the two-dimensional DPCM and the standard two-dimensional transform encoders.

We describe an adaptive coding system capable of representing audio frequency signals in a wide variety of digital code formats. To provide adaptive quantization, the step size is adjusted by voltage controlled amplifiers operating with analog control signals. Sine wave signal-to-noise ratio measurements demonstrate important relationships among the main code classifications: pcm, apcm, dpcm, adpcm. The multipurpose coder has proved a useful laboratory aid in the design of special purpose coders. After adjustment and evaluation of parameters using the multipurpose coder one proceeds to an economical, specialized design.

A new facsimile source coding algorithm, called twodimensional (2-D) delta-mod (Δmod), is presented. The algorithm is based on conventional run length coding. Additional compression is achieved by vertically delta-modulating the horizontal run lengths. The delta-modulation introduces a distortion into the image which can be traded-off versus the rate of transmission. Cumulative error is prevented, as in conventional Δ mod, by including the (run length) quantizer in the feedback loop. Some parametric results are presented

A new approach is presented to the digitization and compression of a class of voiceband modem signals. The approach, baseband residual vector quantization (BRVQ), relies heavily on the simple structure present in a modem signal. After the signal is converted to baseband, the magnitude sequence and the sequence of residuals obtained when the phase within each baud of the baseband signals is modeled by a straight line are separately vector quantized. Carrier frequency estimation and baud-rate classification schemes that were designed to carry out these operations are described. Experimental results show that the performance of the BRVQ system at and below 16 kb/s is better than that of a previously developed vector quantization scheme that has itself been shown to outperform traditional speech-compression techniques such as adaptive predictive coding, adaptive transform coding, and subband coding when these techniques are used to compress modem signals. >

An Adaptive Delta Modulator and demodulator are used as the first and last stages in a system for coding and decoding telephone signals into \mu = 255 Companded Pulse Code Modulation. The system objectives are to devise an economic coder and decoder that is reliable, free of potentiometer adjustments, and convenient for automated manufacturing for large quantity production. The strategy is a shift of circuit emphasis from analog to digital in order to take full advantage of low-cost, low-speed digital processing technology such as MOS/LSI to achieve the desired objectives. The system structure, digital signal processing, system implementation, and performance of the prototype are discussed in this paper.

This paper describes a minicomputer facility developed to aid in the evaluation of the grade-of-service impact of digital codecs. Two minicomputers are interfaced with 15 bit A/D and D/A converters so that an analog signal such as speech can be quantized and stored in real time at sampling rates up to 72 kHz. The acquired digital samples can then be processed by various PCM, ADPCM, and ADM algorithms programmed on the system. After the processing is completed, the facility can automatically generate high quality audio tapes which are suitable for subjective evaluation in an absolute judgment or balance test format. The two minicomputers operate on a stand-alone basis so that the capability exists for simulating either similar or dissimilar tandem encodings in a synchronous or asynchronous mode. A few sample outputs of the facility are also given in the form of subjective test results for single and tandem encodings of μ255 PCM and Nearly Instantaneous Companded (NIC) PCM.

The voice quality of several 9.6 - 32 kbit/s coders is determined with an extensive set of subjective listening tests. Single encodings of μ255 PCM, adaptive differential PCM (ADPCM), subband coding (SBC), vocoder-driven adaptive transform coding (ATC), adaptive predictive coding (APC), and time domain harmonic scaling combined with SBC are compared in an idealized situation, that is, no added impairments. It is shown that single encodings of modest complexity 32 kbit/s coders such as ADPCM and SBC and more complex 24 kbit/s coders such as vocoder-driven ATC and APC offer quality nearly equivalent to 64 kbit/s μ255 PCM. However, these conclusions are drawn in the absence of a realistic telephone network where tandem encodings, delay limitations, and nonvoice signals exist. Tandem encodings of 64 kbit/s μ255 PCM, 32 kbit/s ADPCM, 16 kbit/s SBC, and 16 kbit/s APC are also evaluated. These 32 kbit/s and 16 kbit/s coders offer degraded tandem performance as compared to 64 kbit/s PCM, with the exception of synchronous tandeming of 32 kbit/s ADPCM with 64 kbit/s PCM where several encodings are subjectively equivalent to a single encoding of 32 kbit/s ADPCM.

The multipath tree-encoding of speech at 8 kbits/s is investigated. Tree coding proceeds along the lines of Anderson, et al, but at this lower bit rate, frequency weighting of the error process and adaptation of the coding process are found to be beneficial. Coding results for a stationary speech-like source are found to agree well with rate-distortion theoretic ideas, and when applied to speech, tree coding at 8000 bits/s yielded frequency-weighted SNR's of 15-20 dB.

The purpose of this paper is to quantitatively evaluate the improvement that can be obtained, in the coding of graphics, by using more sophisticated encoding schemes than run-length. These schemes are now well within the reach of today's technology. In the broad class of encoders by coordinates, three isoentropic encoding schemes are considered: 1) encoding of isolated points, 2) encoding of unidimensional patterns, 3) encoding of two-dimensional patterns. Although the three systems are all conceptually straightforward, they require an increasing complexity of encoding-decoding operations. This complexity is balanced, however, by a larger compression factor for the more complex schemes. The results obtained with these encoding schemes are finally compared to those of a run-length coding scheme for the case of a first-order Markov model of the source.

Design algorithms and simulation results are presented for vector quantizers for Fourier transformed data. Transforming the data prior to quantization has two potential advantages. First, each sample in the transform domain depends on many samples in the original domain. Thus, even scalar quantization in the transform domain is a form of vector quantization or block source coding in the original waveform domain and the basic coding theorems of information theory show that such block codes can provide better performance than scalar codes, even for memoryless sources. Second, vector quantization of Fourier transformed speech waveforms provides distinctly better subjective quality than ordinary vector quantization of the waveform using codes of comparable complexity. While the system is, of course, more complicated due to the need to take Fourier transforms, its envisioned application is as a coder for the output of FFT chips currently available or under development. The proposed implementation of a Fourier transform vector quantizer (FTVQ) uses a product code structure, providing different codes for different coefficient vectors corresponding to different frequency bands. This is a form of subband coding and yields a simple means of optimizing bit allocations among the subcodes. Two coding structures with corresponding distortion measures are considered: those that quantize vectors of pairs of real and imaginary coefficients and those that quantize separate vectors of magnitude and phase coefficients. Both structures yield good performance for the given complexity in comparison to waveform vector quantizers. For speech coding, a magnitude-phase FTVQ yields better subjective quality than a real-imaginary FTVQ when the rate allocation is properly chosen.

In orthogonal transform coding of NTSC video signal, the data are processed in blocks. Processing a block of data that is maximally correlated leads to larger compression. This correspondence describes a new architecture for arranging the pixels in a block that yields higher correlation than the adjacent pixel blocks. The data are processed using adaptive, intrafield, discrete cosine transform, variable bit allocation coding. In subjective tests good quality pictures were obtained for an average of about 2 bits/pel for intrafield processing.