Quantization Distortion Research Articles

Incorporating spectral dynamics into LSF vector quantization with error shaping

This paper proposes an innovative technique to incorporate the information of spectral dynamics into the line spectrum frequency (LSF) vector quantization (VQ). This technique is based on a modified weighted log-spectral distortion (MWLSD) measure. It can be used to shape the spectral quantization distortion distribution into any frequencydependent shaping curve, and simultaneously reduce the spectral dynamics distortion between quantized spectra and unquantized spectra. To reduce the high computational complexity of the MWLSD measure during the search procedure in the LSF VQ, a quadratically weighted distortion (QWD) measure used to approximate the MWLSD measure is derived based on the theoretical analysis of the MWLSD measure. A simplified quadratically weighted distortion (SQWD) measure is also proposed to further reduce the computational complexity of the QWD measure for practical applications, whose computational complexity is almost equal to that of weighted mean square error (WMSE) measure. Three experiments are performed to verify the proposed technique in the LSF VQ.

Recognizing GSM digital speech

The Global System for Mobile (GSM) environment encompasses three main problems for automatic speech recognition (ASR) systems: noisy scenarios, source coding distortion, and transmission errors. The first one has already received much attention; however, source coding distortion and transmission errors must be explicitly addressed. In this paper, we propose an alternative front-end for speech recognition over GSM networks. This front-end is specially conceived to be effective against source coding distortion and transmission errors. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bitstream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant advantages. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion as a result of the encoding-decoding process. Second, when transmission errors occur, our front-end becomes more effective since it is not affected by errors in bits allocated to the excitation signal. We have considered the half and the full-rate standard codecs and compared the proposed front-end with the conventional approach in two ASR tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated channel conditions. Furthermore, the disparity increases as the network conditions worsen.

A Multigrid Approach to the Scalar Quantization Problem

A multigrid framework for the one-dimensional (scalar) fixed-rate quantization problem is presented. The framework is based on the Lloyd-Max iterative process, which is a central building block in many quantization algorithms. This process iteratively improves a given initial solution and generally converges to a local minimum of the quantization distortion. Contrary to the classical Lloyd-Max process, the convergence of the multigrid algorithm is practically independent of the number of representation levels sought. Using this approach, a local minimum is reached at the cost of just a few Lloyd-Max iterations. The complexity of the proposed method is O(n) operations for the continuous case and 3N+O(n) for the discrete case, where n is the number of representation levels sought and N is the size of the discrete probability density function. In addition to its independent attributes, this work is a precursor to the more important vector quantization problem, for which a multiscale framework is also being developed.

Operational distortion–quantization curve-based bit allocation for smooth video quality

Quality fluctuation has a major negative effect on subjective video quality. A desirable single-pass frame-level constant-distortion bit allocation scheme is proposed in the paper for smooth video quality throughout the video sequence. The average distortion of all previous coded frames is taken as the target distortion for the current frame. According to the linear rate control algorithm [Z. He, S.K. Mitra, A linear source model and a unified rate control algorithm for DCT video coding, IEEE Trans. Circuits Syst. Video Technol. 12 (2002) 970–982; Z. He, S.K. Mitra, Optimum bit allocation and accurate rate control for video coding via ρ domain source modeling, IEEE Trans. Circuits Syst. Video Technol. 12 (2002) 840–849], the distortion and rate are exponential and linear functions of the number of zero coefficients, respectively. Based on the distribution of the absolute DCT coefficients, an operational distortion–quantization stepsize ( D– Q) relationship curve can be established quickly. With the target distortion and operational D– Q curve, we then derive the close-form formulas for estimating the number of zero coefficients and the slope θ in the linear rate model, as well as the bit budget for the current frame. Experimental results show that the proposed constant-distortion (but variable rate) bit allocation scheme provides much smoother video quality on all test video sequences than the constant bit allocation scheme that has been used in many standard video coding reference software.

An Efficient Representation Method for ICLD with Robustness to Spectral Distortion

The inter-channel level difference (ICLD) is a cue parameter to estimate spectral information in binaural cue coding that has been recently in the spotlight as a multichannel audio signal compression technique. Even though the ICLD is an essential parameter, it is generally distorted by quantization. In this paper, a new modified ICLD representation method to minimize the quantization distortion is proposed by adopting a flexible determination of the reference channel and the unidirectional quantization scheme. Our experimental result confirms that the proposed method improves the multichannel audio output quality even with the reduced bit-rate.

Bounds on the Performance of Vector-Quantizers Under Channel Errors

Vector quantization (VQ) is an effective and widely known method for low-bit-rate communication of speech and image signals. A common assumption in the design of VQ-based communication systems is that the compressed digital information is transmitted through a perfect channel. Under this assumption, quantization distortion is the only factor in output signal fidelity. Moreover, the assignment of channel symbols to the VQ reconstruction vectors is of no importance. However, under physical channels, errors may be present, causing degradation in overall system performance. In such a case, the effect of channel errors on the coding system performance depends on the index assignment of the reconstruction vectors. The index assignment problem is a special case of the Quadratic Assignment Problem (QAP) and is known to be NP-complete. For a VQ with N reconstruction vectors there are N! possible assignments, meaning that an exhaustive search over all possible assignments is practically impossible. To help the VQ designer, we present in this correspondence lower and upper bounds on the performance of VQ systems under channel errors, over all possible assignments. The bounds coincide with a general bound for the QAP. Nevertheless, the proposed derivation allows us to compare the bounds with published results on VQ index assignment. A related expression for the average performance is also given and discussed. Special cases and numerical examples are given in which the bounds and average performance are compared with index assignments obtained by known algorithms.

Dynamic contrast-based quantization for lossy wavelet image compression

This paper presents a contrast-based quantization strategy for use in lossy wavelet image compression that attempts to preserve visual quality at any bit rate. Based on the results of recent psychophysical experiments using near-threshold and suprathreshold wavelet subband quantization distortions presented against natural-image backgrounds, subbands are quantized such that the distortions in the reconstructed image exhibit root-mean-squared contrasts selected based on image, subband, and display characteristics and on a measure of total visual distortion so as to preserve the visual system's ability to integrate edge structure across scale space. Within a single, unified framework, the proposed contrast-based strategy yields images which are competitive in visual quality with results from current visually lossless approaches at high bit rates and which demonstrate improved visual quality over current visually lossy approaches at low bit rates. This strategy operates in the context of both nonembedded and embedded quantization, the latter of which yields a highly scalable codestream which attempts to maintain visual quality at all bit rates; a specific application of the proposed algorithm to JPEG-2000 is presented.

Multistep optimal analog-to-digital conversion

An important aspect of analog-to-digital conversion is the impact of quantization errors. This paper outlines how finite horizon constrained optimization methods can be utilized to design converters which minimize a weighted measure of the quantization distortion. We propose a novel converter, which can be implemented as a feedback loop. It embeds /spl Sigma//spl Delta/ conversion in a more general setting and typically provides better performance. We also examine the role played by the associated design parameters in ensuring error convergence.

Joint watermarking and compression using scalar quantization for maximizing robustness in the presence of additive Gaussian attacks

In joint watermarking and compression (JWC), a key process is quantization which embeds watermarks into a host signal while digitizing the host signal subject to requirements on the embedding rate, compression rate, quantization distortion, and robustness. Using fixed-rate scalar quantization for watermarking and compression, in this paper, we mainly consider how to design binary JWC systems to maximize the robustness of the systems in the presence of additive Gaussian attacks under constraints on the compression rate and quantization distortion. We first investigate optimum decoding of a binary JWC system, and demonstrate by experiments that in the distortion-to-noise ratio (DNR) region of practical interest, the minimum distance (MD) decoder achieves performance comparable to that of the maximum likelihood decoder in addition to having advantages of low computation complexity and being independent of the statistics of the host signal. We then present optimum binary JWC encoding schemes using fixed-rate scalar quantization and the MD decoder. Simulation results show that optimum binary JWC systems using nonuniform quantization are better than optimum binary JWC systems using uniform quantization. Furthermore, in comparison with separate watermarking and compression systems, optimum binary JWC systems using nonuniform quantization achieve significant DNR gains in the DNR region of practical interest. Finally, spread transform dither modulation is applied to improving the robustness of the JWC systems at low DNRs.

Modified TMN8 Rate Control for Low-Delay Video Communications

The existing macroblock-layer rate control schemes in the literature calculate quantization parameters of all macroblocks (MBs) in a frame in a raster scan order, and then encode the MBs in the same order. Actually, the quantization distortion is heavily dependent upon the coding order of MBs. This work investigates the relationship between quantization distortion and the coding order. Then we present a scheme where we modify the encoding order of MBs in TMN8 to favor the more complex MBs. We implement TMN8 and the modified version in H.263 video codec. The experimental results indicate that our scheme achieves average PSNR gain of 1.05 dB over TMN8. In addition, it performs better in buffer overflow and underflow, and the average bit rate achieved is closer to the target channel rate. The new rate control scheme is fully compliant to H.263 coding standard.

Optimum quantization and its applications

Minimum sums of moments or, equivalently, distortion of optimum quantizers play an important role in several branches of mathematics. Fejes Tóth's inequality for sums of moments in the plane and Zador's asymptotic formula for minimum distortion in Euclidean d-space are the first precise pertinent results in dimension d⩾2. In this article these results are generalized in the form of asymptotic formulae for minimum sums of moments, resp. distortion of optimum quantizers on Riemannian d-manifolds and normed d-spaces. In addition, we provide geometric and analytic information on the structure of optimum configurations. Our results are then used to obtain information on (i) the minimum distortion of high-resolution vector quantization and optimum quantizers, (ii) the error of best approximation of probability measures by discrete measures and support sets of best approximating discrete measures, (iii) the minimum error of numerical integration formulae for classes of Hölder continuous functions and optimum sets of nodes, (iv) best volume approximation of convex bodies by circumscribed convex polytopes and the form of best approximating polytopes, and (v) the minimum isoperimetric quotient of convex polytopes in Minkowski spaces and the form of the minimizing polytopes.

Implementation of digital HDTV encoder with parallel sub-picture encoding modules and its joint bit-allocation strategy

Parallel processing is a feasible scheme for a digital HDTV encoder, to get round the dilemma in high-speed digital processing circuitry and real-time compression. This paper suggests an implementation procedure and a novel bit-allocation strategy for a digital high definition television (HDTV) encoder system with parallel processing architecture based on six horizontal strips division. Multiple sub-pictures encoding modules (SEMs) perform MPEG-2 coding respectively and simultaneously. Owing to the inherent deficiencies of MPEG-2 Test Model 5 (TM5) rate control scheme, how to allocate bit-rate among sub-pictures would become an inevitable challenge, which might behave with the coding quality to decrease worse and the buffer to underflow at scene changes, moreover give birth to non-consistent sub-pictures visual quality and dynamic quality variation in a composite HDTV frame on subjective and objective evaluation. We adapt a hierarchical joint optimized bit-allocation with sub-pictures' average complexity measure and average bits per pixel in terms of their average quantization distortion, moreover incorporates scene detection to alleviate a possible worse sub-pictures quality inconsistency. In the paper, we describe an elaborate procedure including general framework, sub-pictures division module, sub-picture encoding module and sub-pictures synthesis module, then deduce the joint bit-allocation strategy for sub-pictures encoding and the auxiliary rate adaptive procedure for scene changes. Experimental results demonstrate that our proposed scheme not only alleviates the boundary effect, but also promises the sub-pictures quality consistency. The proposed scheme might be devoted to the multiprogram broadcast application and the multiple access sceneries.

Speaker change detection and speaker clustering using VQ distortion measure

AbstractThis paper addresses the problem of the detection of speaker changes and clustering speakers when no information is available regarding speaker classes or even the total number of classes. This study provides preprocessing for a method which adapts speaker information based on incremental on‐line speaker clustering. We assume that no previous information on speakers is available (no speaker model, no training phase) and that people do not speak simultaneously. The aim is to apply speaker grouping information to speaker adaptation for speech recognition.We use Vector Quantization (VQ) distortion as the criterion. A speaker model is created from successive utterances as a codebook by a VQ algorithm, and the VQ distortion is calculated between the model and an utterance.The results of an experiment on speaker detection and speaker clustering are presented. The speaker change detection experiment was compared with results of the Generalized Likelihood Ratio (GLR) and Bayesian Information Criterion (BIC). By using GLR and BIC, we obtained F‐measures of 75.8 and 81.4, respectively. On the other hand, we obtained an F‐measure of 84.4 by the proposed method. Furthermore, by a combination of the method with an acoustic back‐off method, we obtained a measure of 93.1 and a classification rate of 97.7%. These results show the superiority of our proposed method. Finally, we demonstrate the validity of our proposed method by experiments on speech recognition using on‐line speaker adaptation. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(13): 25–35, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10488

Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions.

Quantization of the coefficients within a discrete wavelet transform subband gives rise to distortions in the reconstructed image that are localized in spatial frequency and orientation and are spatially correlated with the image. We investigated the detectability of these distortions: Contrast thresholds were measured for both simple and compound distortions presented in the unmasked paradigm and against two natural-image maskers. Simple and compound distortions were generated through uniform scalar quantization of one or two subbands. Unmasked detection thresholds for simple distortions yielded contrast sensitivity functions similar to those reported for 1-octave Gabor patches. Detection thresholds for simple distortions presented against two natural-image backgrounds revealed that thresholds were elevated across the frequency range of 1.15-18.4 cycles per degree with the greatest elevation for low-frequency distortions. Unmasked thresholds for compound distortions revealed relative sensitivities of 1.1-1.2, suggesting that summation of responses to wavelet distortions is similar to summation of responses to gratings. Masked thresholds for compound distortions revealed relative sensitivities of 1.5-1.7, suggesting greater summation when distortions are masked by natural images.

Performance evaluation of an adaptive-rate MPEG encoder matching intserv traffic constraints

Promoting the evolution of the Internet from a simple data network to a true multiservice network constitutes a challenging task. To this end, the Internet Engineering Task Force (IETF) has set up the Integrated Services (IntServ) and Differentiated Services (DiffServ) Working Groups, with the goal of defining a next-generation Internet, in which traditional best-effort datagram delivery and additional enhanced quality of service delivery classes coexist. The IntServ framework, in particular, is designed to be used in the access network, and requires a traffic source with the capability of matching the traffic characteristics declared to the network, TSpec. We propose to use the rate control facility, usually implemented in current MPEG encoders to provide a constant bit rate, to shape the output traffic according to the declared TSpec while maintaining an acceptable perceived image quality. In order to assess this scenario, we introduce an SBBP/D/N/K queueing system, where the SBBP (switched batch Bernoulli process) emission is varied according to the quantizer scale parameter chosen by the addressed rate control mechanism. The analytical framework allows us: 1) to evaluate system performance in terms of both the marking probability of nonconforming output traffic and the quantization distortion introduced by the encoder; 2) to choose the TSpec parameters to be declared such that given performance parameters are respected.

Time-varying MMSE modulated lapped transform and its applications to transform coding for speech and audio signals

The time-varying modulated lapped transform (MLT) is used in speech and audio coding schemes to adjust the time-frequency resolution, to eliminate pre-echoes in the reconstructed signal, and to improve the coding quality. In order to maintain the perfect-reconstruction property in transition periods, an asymmetrical window has to be used at cost of poorer frequency characteristics. We firstly generalize a window-design method for transition periods in the time-varying MLT with a rigorous proof of its PR property, then present a new window-design method, with which the prototype window is so designed that the total reconstruction distortion in presence of coefficient quantization is minimized. This leads to the time-varying minimum mean-square error (MMSE) MLT. Experiments have shown that the designed windows have better frequency characteristics than the sine window in both transition and regular periods. A general formulation of the quantization distortion for different quantization-error models and for all coding systems is given. A simplified optimal window-design algorithm without direct minimization of the distortion equation is suggested. As an example a transform-coding scheme with time-varying MMSE MLT for speech and audio signals is presented.

Psychophysically derived quantisation model for efficient DWT image coding

An efficient method for the optimum quantisation of the luminance and chrominance components for discrete wavelet transform (DWT) still image coding, based on current psychophysical evidence, is described. Its practical application to image compression is presented. This new approach is further supported by experimental work which compares perceived DWT image quality with conventional JPEG-encoding, that is block-based discrete cosine transform (DCT) coding, on the basis of quantisation distortion.

Tspec enforcement for MPEG video transmission over the next generation Internet: an analytical framework

The evolution of the Internet from a simple data network into a true multiservice network today constitutes a challenging task. To this end, the Internet engineering task force (IETF) has set up the integrated services (intserv) working group, with the goal of defining a next generation Internet, in which traditional best-effort datagram delivery and additional enhanced quality of service delivery classes coexist. In this framework it is necessary to provide a traffic source with the capability of matching the traffic characteristics, Tspec, declared to the network. Current MPEG encoders implement feedback laws which usually take into account the state of the encoder output buffer to provide a constant output bit rate. In this paper we propose to use this encoder facility to shape the output traffic according to the declared Tspec while maintaining an acceptable perceived image quality, and we introduce an analytical tool to evaluate feedback laws which provide this target efficiently. To this end an SBBP/D/N/K queueing system is used where the SBBP arrival process is varied according to the quantizer scale parameter chosen by the addressed feedback law at the frame level. The analytical framework allows us to evaluate system performance in terms of both marking probability, defined as the probability that the output traffic is not compliant with the specifications, and quantization distortion.

Recognizing voice over IP: a robust front-end for speech recognition on the world wide web

The Internet Protocol (IP) environment poses two relevant sources of distortion to the speech recognition problem: lossy speech coding and packet loss. In this paper, we propose a new front-end for speech recognition over IP networks. Specifically, we suggest extracting the recognition feature vectors directly from the encoded speech (i.e., the bit stream) instead of decoding it and subsequently extracting the feature vectors. This approach offers two significant benefits. First, the recognition system is only affected by the quantization distortion of the spectral envelope. Thus, we are avoiding the influence of other sources of distortion due to the encoding-decoding process. Second, when packet loss occurs, our front-end becomes more effective since it is not constrained to the error handling mechanism of the codec. We have considered the ITU G.723.1 standard codec, which is one of the most preponderant coding algorithms in voice over IP (VoIP) and compared the proposed front-end with the conventional approach in two automatic speech recognition (ASR) tasks, namely, speaker-independent isolated digit recognition and speaker-independent continuous speech recognition. In general, our approach outperforms the conventional procedure, for a variety of simulated packet loss rates. Furthermore, the improvement is higher as network conditions worsen.

Low-delay rate control for DCT video coding via ρ-domain source modeling

By introducing the new concepts of characteristic rate curves and rate curve decomposition, a generic source-modeling framework is developed for transform coding of videos. Based on this framework, the rate-quantization (R-Q) and distortion-quantization (D-Q) functions (collectively called R-D functions in this work) of the video encoder can be accurately estimated with very low computational complexity before quantization and coding. With the accurate estimation of the R-Q function, a frame-level rate control algorithm is proposed for DCT video coding. The proposed algorithm outperforms the TMN8 rate control algorithm by providing more accurate and robust rate regulation and better picture quality. Based on the estimated R-D functions, an encoder-based rate-shape-smoothing algorithm is proposed. With this smoothing algorithm, the output bit stream of the encoder has both a smoothed rate shape and a consistent picture quality, which are highly desirable in practical video coding and transmission.