Bit allocation

Layanan streaming musik bergantung pada adaptive bitrate (ABR) streaming dan kompresi audio variable bitrate (VBR) untuk menyesuaikan kualitas dengan kondisi jaringan. Akan tetapi, baik algoritma ABR di level jaringan maupun encoder di level sinyal mengalokasikan bit berdasarkan karakteristik sinyal, bukan signifikansi perseptual musikal, yaitu seberapa penting suatu bagian lagu bagi pendengar. Tujuan penelitian adalah menganalisis kesenjangan tersebut secara eksplisit dan menyajikan indikasi empiris awal melalui studi kasus. Metode yang digunakan adalah pendekatan deskriptif kualitatif yang dipadukan dengan audit alokasi bit pada dua karya musik orisinal dari genre kontras, yaitu sebuah komposisi orkestra (11 segmen) dan sebuah drop melodic dubstep (33 segmen), yang di-encode ke MP3 VBR pada dua tingkat kualitas. Bitrate per segmen, fitur sinyal seperti spectral entropy, dan skor salience dianalisis menggunakan korelasi Spearman serta korelasi parsial dengan mengontrol kompleksitas sinyal. Hasil menunjukkan bahwa salience bukan penentu alokasi bit: keselarasan positif pada orkestra (rho = 0,35) runtuh menjadi mendekati nol setelah kompleksitas dikontrol (rho parsial =-0,22), sedangkan pada EDM bit justru menjauhi bagian terpenting (rho parsial =-0,64). Kesimpulannya, encoder VBR buta terhadap signifikansi perseptual karena menggerakkan alokasi bit melalui kompleksitas sinyal, sehingga memperkuat urgensi pengembangan mekanisme alokasi bit yang sadar-salience pada pengiriman audio musik adaptif.

This is the second part of a two-part paper on optimal design of limited feedback single-user and multiuser spatial multiplexing systems. The first part of the paper studies the single-user system and this part addresses the multiuser case. The problem is cast in form of minimizing the average transmission power at the base station subject to the outage probability constraints at the users' side. The optimization is over the power control function at the base station as well as the users' channel quantization codebooks. The base station has M antennas and serves M single-antenna users, which share a common feedback link with a total rate of B bits per fading block. We first fix the quantization codebooks and study the optimal power control problem which leads to an upper bound for the average transmission sum power. The upper bound solution is then used to optimize the quantization codebooks and to derive the optimal bit allocation laws in the asymptotic regime of B → ∞. The paper shows that for channels in the real space, the optimal number of channel direction quantization bits should be M -1 times the number of channel magnitude quantization bits. It is shown that the users with higher requested QoS (lower target outage probabilities) and higher requested downlink rates (higher target SINR's) should receive larger shares of the feedback rate. The paper further shows that, for the target QoS parameters to be feasible, the total feedback bandwidth should scale logarithmically with γ, the geometric mean of the target SINR values, and 1/q, the geometric mean of the inverse target outage probabilities. Moreover, the minimum required feedback rate increases if the users' target parameters deviate from the average parameters γ and q. Finally, we show that, as B increases, the multiuser system performance approaches the performance of the perfect channel state information system as 1/q • 2 -B M 2 .

This paper reports two efficient quadtree-based algorithms for variable-size block matching (VSBM) motion estimation. The schemes allow the dimensions of blocks to adapt to local activity within the image, and the total number of blocks in any frame can be varied while still accurately representing true motion. This permits adaptive bit allocation between the representation of displacement and residual data, and also the variation of the overall bit-rate on a frame-by-frame basis. The first algorithm computes the optimal selection of variable-sized blocks to provide the best-achievable prediction error under the fixed number of blocks for a quadtree-based VSBM technique. The algorithm employs an efficient dynamic programming technique utilizing the special structure of a quadtree. Although this algorithm is computationally intensive, it does provide a yardstick by which the performance of other more practical VSBM techniques can be measured. The second algorithm adopts a heuristic w...

This paper considers discrete multitone (DMT) modulation for multiuser communications where different users are supported by the same system. These users may have differing quality of service (QoS) requirements, as quantified by their respective bit rate and symbol error rate specifications. Our goal is to minimize the transmitted power given the QoS specifications for the different users, subject to the knowledge of colored interference at the receiver input. In particular we find an optimum bit loading scheme that distributes the bit rate transmitted across the various subchannels belonging to the different users, and subject to this bit allocation, determine an optimum transceiver.

In this paper, we consider the problem of optimal bit allocation for a multiuser multicarrier communications. Some of the existing papers comment, without a proof, on the intractability of the problem and provide algorithms resulting in suboptimal bit allocation to reduce the computation complexity. A formal proof for classifying this problem as being NP-hard is presented in this article.

In this paper we investigate a special-purpose application of MPEG-1 layer II audio streaming. First, we discuss how two or more already coded MPEG-audio bitstreams can be manipulated and mixed within the coded subband domain by using an appropriate algorithm for combining and recalculating the bit allocation. Next, we will show that very significant speedups can be obtained compared with mixing in the temporal domain. We will also illustrate that, at the same time, the system can act as a bit rate scaling device, using one of the bit allocation-combination algorithms which we implemented. The results obtained with these different algorithms are briefly discussed and compared. Finally, we report on how the developed software was integrated into an internet audio streaming system, which is now able to allow simple, yet efficient, real-time mixing of several MPEG-audio coded signals.

Computer modeling programs that generate threedimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.

It is often requested to get an analytical formula for the throughput (i.e. TBS (Transport Block Size)) vs. SINR, MIMO rank, and modulation order, either as drive test results or as an analytical formula.
In this white paper a common way is recommended to use the Shannon-Hartley theorem, which relates capacity to bandwidth and SINR.

When communicating at a very-low bit-rate, video coders are unable to preserve high visual quality for all images. A selection of key regions according to human viewing and understanding may therefore be useful: it allows extracting essential features and to code them with a high quality, while the remainder of the image is coarsely transmitted. Such an approach requires a signal decomposition allowing an adaptive spatial variant bit allocation. Matching Pursuits (MP) is an iterative procedure leading to such a signal representation. Incorporated within a motion compensated video codec, MP allows for adaptive representation of the Displaced Frame Difference. Bit allocation procedures for Matching Pursuits differ from the ones used for DCT-or other transform-based signal representations. For transformbased methods, the signal is first projected on a complete set of orthogonal base functions. Coefficients are then quantized. The quantization selects which information is transmitted. So, the selection is constrained by the chosen transform. On the contrary, MP explicitly select the information to be transmitted among a large and overcomplete set of functions and quantize it according to a fixed and constant step. For MP, bit allocation is equivalent to function selection. This makes Matching Pursuits well-suited for spatial variant bit allocation, since functions matched to important objects can be chosen. In this paper, we first show the abilities of Matching Pursuits to allocate an available bit-budget according to a semantic understanding of the scene. This semantic information can be provided either automatically or interactively. Second, the possibility to incorporate perceptive criteria within the MP coding algorithm is investigated.

Rate control is a complicated problem in the H.264/AVC coding standard, extra computation is usually needed for the existing rate control schemes to estimate the complexity of frames or macroblocks (MBs). However, during transcoding, information from precoded video could be used to simplify the rate control. In this paper, we propose a low-complexity rate control scheme for transcoding from H.263 to H.264/AVC. The relationship between the rate of the precoded video and both the rate and distortion of the transcoded video are studied. By using only the rate information from the precoded video, we introduce a row-layer bit allocation and perform average rate shaping across a row of MBs. Estimation error diffusion is also introduced. The proposed scheme has sufficiently lower computational complexity than other methods as there is no explicit complexity measurement of MBs and complicated parameters updating. Experimental results show the effectiveness of the proposed scheme.

Rate control is a complicated problem in the H.264/AVC coding standard, extra computation is usually needed for the existing rate control schemes to estimate the complexity of frames or macroblocks (MBs). However, during transcoding, information from precoded video could be used to simplify the rate control. In this paper, we propose a low-complexity rate control scheme for transcoding from H.263 to H.264/AVC. The relationship between the rate of the precoded video and both the rate and distortion of the transcoded video are studied. By using only the rate information from the precoded video, we introduce a row-layer bit allocation and perform average rate shaping across a row of MBs. Estimation error diffusion is also introduced. The proposed scheme has sufficiently lower computational complexity than other methods as there is no explicit complexity measurement of MBs and complicated parameters updating. Experimental results show the effectiveness of the proposed scheme.

A low complexity hierarchical quadrature amplitude modulation (QAM) symbol bits allocation algorithm for unequal error protection of video transmission over wireless channels is proposed in this paper. An unequal error protection (UEP) scheme using hierarchical QAM, which takes into consideration the non-uniformly distributed importance of intracoded frame (I-frame) and predictive coded frame (P-frame) in a group of pictures (GOP), is first proposed. In order to optimally allocate the hierarchical QAM's high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H.264/AVC video, a generic solution for optimal allocation of hierarchical QAM's high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H.264/AVC video is then proposed. Finally, a low complexity symbol bits allocation algorithm, namely ranking search algorithm, which reduces the computational complexity of the proposed optimal symbol bits allocation algorithm, is proposed. Simulation results show that our proposed UEP scheme outperforms the classical equal error protection (EEP) scheme and also the previous UEP scheme.

This paper proposes new buffer and video object distortion feedback compensation mechanisms for efficiently dealing with deviations between the ideal and the actual behavior of video scene encoders when jointly encoding multiple arbitrarily shaped video objects in the context of compliant low-delay object-based MPEG-4 video coding. The proposed solution computes target buffer occupancies for each encoding time instant based on the amount and complexity of the video data to encode, and the bit allocation for each encoding time instant is feedback adjusted according to deviations relatively to this ideal behavior. Additionally, each video object bit allocation is also feedback adjusted based on the relative distortion of the various video objects in the scene. The proposed solution outperforms the non-normative MPEG-4 reference rate control algorithm for a wide range of bit rates and spatio-temporal resolutions, for typical test sequences.

This paper studies the quality of multimedia content at very low bitrates. We carried out subjective experiments for assessing audiovisual, audio-only, and video-only quality. We selected content and encoding parameters that are typical of mobile applications. Our focus were the MPEG-4 AVC (a.k.a. H.264) and AAC coding standards. Based on these data, we first analyze the influence of video and audio coding parameters on quality. We investigate the optimal trade-off between bits allocated to audio and to video under global bitrate constraints. Finally, we explore models for the interactions between audio and video in terms of perceived audiovisual quality.

We carried out a number of subjective experiments for audiovisual, audio-only, and video-only quality assessment. We selected content and encoding parameters at very low bitrates that are typical of mobile applications. Using these data, we explore the influence of video codecs and frame rate as well as audio channels and sampling rate on quality. Finally, the optimal trade-off between bits allocated to audio and video inside a bitstream is investigated.

In this paper, we study the problem of backhaul sharing in Network MIMO. In case of a backhaul of limited number of bits, we investigate how to allocate these bits jointly with the base-stations power among users in order to maximize the sum-rate under fairness constraints. Firstly, we study this problem with the assumption of one user per cell. We find that binary allocation of power is optimal. Then, the multi-user case is considered. A solution of the optimization problem is developed under high signal-to-interference and noise ratio(SINR). We prove that under these assumptions, backhaul bits allocation among the cells or among the users of each cell has no effect on the sum-rate of system. Hence, allocating these bits in order to achieve fairness conditions is possible without any loss in the sum-rate.

This paper addresses the problem of computing the optimum bit allocation in a subband coder with low selectivity filters, while maintaining the power of quantization noise below a given value. A low complexity strategy that takes into account the frequency responses of the synthesis filter bank, is proposed. The Lagrange multiplier method is used to obtain the optimum bit distribution. The number of bits to be allocated to a subband depends only on the frequency response of that subband, on the variance of the corresponding subband signal, on the maximum allowed noise power, and on the decimation factors of all the subbands.

In this paper, we present a theoretical analysis of the distortion in multi-layer coding structures. Specifically, we analyze the prediction structure used to achieve temporal, spatial, and quality scalability of scalable video coding (SVC), and show that the average peak-signal-to-noise (PSNR) of SVC is a weighted combination of the bit rates assigned to all the streams. Our analysis utilizes the end user's preference for certain resolutions. We also propose a rate-distortion (R-D) optimization algorithm, and compare its performance with that of a state-of-the-art scalable bit allocation algorithm. The reported experiment results demonstrate that the R-D algorithm significantly outperforms the compared approach in terms of the average PSNR.

In object-based video, the encoding of the video data is decoupled into the encoding of shape, motion and texture information, which enables certain functionalities like content-based interactivity and scalability. However, the problem of how to jointly encode these separate signals to reach the best coding efficiency has never been solved thoroughly. In this paper, we present an operational ratedistortion optimal bit allocation scheme that provides a solution to this problem. Our approach is based on the Lagrangian relaxation and dynamic programming. Experimental results indicate that the proposed optimal encoding approach has considerable gains over an ad-hoc method without optimization. Furthermore the proposed algorithm is much more efficient than exhaustive search.

MPEG-4 is the first multimedia standard that supports the decoupling of a video object into object shape and object texture information, which consequently brings up the optimal encoding problem for object-based video. In this paper, we present an operational rate-distortion optimal bit allocation scheme between shape and texture for MPEG-4 encoding. Our approach is based on the Lagrange multiplier method, while the adoption of dynamic programming techniques enables its higher efficiency over the exhaustive search algorithm. Our work will not only benefit the further study of joint shape and texture encoding, but also make possible the deeper study of optimal joint source-channel coding of object-based video.

In this paper, we propose an optimal quadtree (QT)based motion estimator for video compression. It is optimal in the sense that for a given bit budget for encoding the displacement vector field (DVF) and the QT segmentation, the scheme finds a DVF and a QT segmentation which minimizes the energy of the resulting displaced frame difference (DFD). We find the optimal QT decomposition and the optimal DVF jointly using the Lagrangian multiplier method and a multilevel dynamic program. We introduce a new, very fast convex search for the optimal Lagrangian multiplier 3 3 3 , which results in a very fast convergence of the Lagrangian multiplier method. The resulting DVF is spatially inhomogeneous, since large blocks are used in areas with simple motion and small blocks in areas with complex motion. We also propose a novel motion-compensated interpolation scheme which uses the same mathematical tools developed for the QT-based motion estimator. One of the advantages of this scheme is the globally optimal control of the tradeoff between the interpolation error energy and the DVF smoothness. Another advantage is that no interpolation of the DVF is required since we directly estimate the DVF and the QT-segmentation for the frame which needs to be interpolated. We present results with the proposed QT-based motion estimator which show that for the same DFD energy the proposed estimator uses about 25% fewer bits than the commonly used block matching algorithm. We also experimentally compare the interpolated frames using the proposed motion compensated interpolation scheme with the reconstructed original frames. This comparison demonstrates the effectiveness of the proposed interpolation scheme.

In object-based video, the encoding of the video data is decoupled into the encoding of shape, motion and texture information, which enables certain functionalities like content-based interactivity and scalability. However, the problem of how to jointly encode these separate signals to reach the best coding efficiency has never been solved thoroughly. In this paper, we present an operational ratedistortion optimal bit allocation scheme that provides a solution to this problem. Our approach is based on the Lagrangian relaxation and dynamic programming. Experimental results indicate that the proposed optimal encoding approach has considerable gains over an ad-hoc method without optimization. Furthermore the proposed algorithm is much more efficient than exhaustive search.

In this paper, we address the fundamental problem of optimally splitting a video sequence into two sources of information, the displaced frame difference (DFD) and the displacement vector field (DVF). We first consider the case of a lossless motion-compensated video coder (MCVC), and derive a general dynamic programming (DP) formulation which results in an optimal tradeoff between the DVF and the DFD. We then consider the more important case of a lossy MCVC, and present an algorithm which solves the tradeoff between the rate and the distortion. This algorithm is based on the Lagrange multiplier method and the DP approach introduced for the lossless MCVC. We then present an H.263-based MCVC which uses the proposed optimal bit allocation, and compare its results to H.263. As expected, the proposed coder is superior in the rate-distortion sense. In addition to this, it offers many advantages for a rate control scheme. The presented theory can be applied to build new optimal coders, and to analyze the heuristics employed in existing coders. In fact, whenever one changes an existing coder, the proposed theory can be used to evaluate how the change affects its performance.

The problem of encoding and transmitting a video sequence over an IP-based wireless network, consisting of both wired and wireless links, is addressed. To combat the different types of packet loss in the heterogeneous network, the use of a product code forward error correction (FEC) scheme capable of providing unequal error protection is considered. At the transport layer, Reed-Solomon (RS) coding is used to provide inter-packet protection. In addition, rate-compatible punctured convolutional (RCPC) coding is ...

This paper investigates the problem of dynamic subcarrier and bit allocation in downlink of Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiple Access (OFDMA) Systems. Using Singular Value Decomposition, the MIMO fading channel of each subcarrier is transformed into an equivalent bank of parallel Single Input Single Output sub-channels. To achieve the capacity bound, one must solve a multiuser subcarrier allocation and the optimal bit allocation jointly. To alleviate the computational complexity of joint subcarrier and bit allocation, several suboptimal solutions have been proposed. These suboptimal solutions handle subcarrier and bits individually. We propose the use of Non-dominated Sorting Genetic Algorithm (NSGA)-II, which is a multi-objective Genetic Algorithm, for joint allocation of bits and subcarriers, in the downlink of MIMO-OFDMA system. NSGA-II is intended for optimization problems involving multiple conflicting objectives. Here the two conflicting objectives are Rate Maximization and Transmit Power Minimization. The simulation results indicate remarkable improvement in terms of convergence over previous approaches involving Evolutionary algorithms. At the same time capacity achieved by the proposed algorithm is found to be comparable with that of previous algorithms.

In this paper, we address the fundamental problem of optimally splitting a video sequence into two sources of information, the displaced frame difference (DFD) and the displacement vector field (DVF). We first consider the case of a lossless motion-compensated video coder (MCVC), and derive a general dynamic programming (DP) formulation which results in an optimal tradeoff between the DVF and the DFD. We then consider the more important case of a lossy MCVC, and present an algorithm which solves the tradeoff between the rate and the distortion. This algorithm is based on the Lagrange multiplier method and the DP approach introduced for the lossless MCVC. We then present an H.263-based MCVC which uses the proposed optimal bit allocation, and compare its results to H.263. As expected, the proposed coder is superior in the rate-distortion sense. In addition to this, it offers many advantages for a rate control scheme. The presented theory can be applied to build new optimal coders, and to analyze the heuristics employed in existing coders. In fact, whenever one changes an existing coder, the proposed theory can be used to evaluate how the change affects its performance.

We present a video coder based on a bit-allocation (BA) scheme for a coding approach where a wavelet-based video compression scheme is used to encode group of frames (GOF). The proposed new BA method utilizes a Lagrangian multiplier technique to determine the optimal bit rate for each frame of a given GOF in a rate versus weighted distortion sense. The proposed baseline coder sequentially employs the application of the wavelet transform on each frame in the group. In the wavelet domain, an optimal-vector BA (rate-allocation strategy) is being used to distribute the bit budget among the frames. The manipulated frames in each group are quantized and coded using techniques from still-image compression. We describe and demonstrate the performance of the proposed algorithm in wavelet-based coding approaches. The first one, a combination of wavelet still compression and optimal BA (WCBA), is based on frame differences and exploits well the wavelet compression characteristics which keeps, for a given bit budget, the most important features. It does not utilize motion-compensation interpolation or a 3-D wavelet decomposition. In cases where "heavy" motion is detected, we extend WCBA into a combination of wavelet still compression, optimal BA, motion compensation with block matching, and error correction (WCBAM), which uses block matching for motion estimation, while the residual error of the compression is reduced by applying error correction in the wavelet domain to reduce temporal redundancies. NOMENCLATURE Group of frames in the video sequence. Frame in the video sequence. Wavelet coefficients of frame. Difference between the wavelet coefficients of and. Output stream of bits from the compression of. Decompressed frame after reconstruction. Wavelet coefficients after the decompression and also the wavelet coefficients of frame Difference between the coefficients of and and also the quantized values of after the decompression. Motion vectors which describe the blocks displacement when predicting from. Compression ratio of frame according to the optimal BA [(26)] Stream of bits that represents the compressed. DWT Discrete wavelet transform. IDWT Inverse DWT. BA Bit allocation. Quantization.

A visual attention-based bit allocation strategy for video compression is proposed. Saliency-based attention prediction is used to detect interesting regions in video. From the top salient locations from the computed saliency map, a guidance map is generated to guide the bit allocation strategy through a new constrained global optimization approach, which can be solved in a closed form and independently of video frame content. Fifty video sequences (300 frames each) and eye-tracking data from 14 subjects were collected to evaluate both the accuracy of the attention prediction model and the subjective quality of the encoded video. Results show that the area under the curve of the guidance map is 0.773 ± 0.002, significantly above chance (0.500). Using a new eye-tracking-weighted PSNR (EWPSNR) measure of subjective quality, more than 90% of the encoded video clips with the proposed method achieve better subjective quality compared to standard encoding with matched bit rate. The improvement in EWPSNR is up to over 2 dB and on average 0.79 dB.

The combination of subband coding and vector quantization can provide a powerful method for compressing color images. The use of properties of the human visual system can increase the performance of such a system and allow one to achieve very high quality reconstructed images at compression ratios exceeding 10:1. In this paper, we design a color subband-vector quantization system, and formulate the bit allocation problem as an optimization problem where the objective function depends on the distortion-rate curves of the quantizers and on a set of perceptual weights. These weights are derived from data provided by experimental measurements [10, 14] of the mean detection threshold of the human visual system for color transitions along the luminance, red-green, and blue-yellow directions. Minimization of the objective function constrained by the desired bit rate gives a perceptually optimal bit allocation. Three subband/VQ cases are examined. In the first two cases (Case 1 and Case 2), the color components of the lowest frequency subband are scalar quantized. Case 1 combines the three color components of each pixel of the higher frequency subbands into a three-dimensional vector, while Case 2 creates four-dimensional vectors from 2 x 2 blocks in each subband color component. The third case (Case 3) is the same as Case 2, except that the chrominance components of the lowest frequency subband are also vector quantized with 2 X 2 blocks in each component. To obtain the required compression ratio and the high color fidelity required for HDTV applications, the vector quantization is done in two different perceptually uniform color spaces, e.l.E. L*a*b* space and AC 1C2 space. Results from these color spaces are compared to results obtained in N.T.S.C. YIQ space.

In this paper we propose a special bit allocation method which can be used in most rate control algorithms in variable rate video applications. In real-time video communication applications, we need a constant short-term average bitrate, while in variable bitrate applications such as streaming and local recording applications, a constant long-term average bitrate is sufficient and more short-term variation in bitrate is acceptable. In comparison with constant bitrate video, a variable bitrate video can provide better visual quality and coding efficiency for compressed video sequences. Furthermore, while more variation in bitrate is possible we have additional degrees of freedom to control the encoding parameters. We propose a special bit allocation algorithm to take advantage of this freedom in variable bitrate video. We introduce a new type of frame namely SPP frame (SPecial P frame) that can be used in combination with I, P, B and other types of frames in different encoders including H.263, MPEG-4 and H.264/AVC encoders. We propose a simple method to implement the SPP frames independently of the rate control algorithm. The experimental results show that the SPP frames can considerably increase the total average quality of variable rate encoded video.

This paper descrihes a novel wavelet based audio synthesis and coding method. The method uses optimal adaptive wavelet selection and wavelet coefficients quantization procedures together with a dynamic dictionary approach. The adaptive wavelet transform selection and transform coefficient bit allocation procedures are designed to take advantage of the masking effect in human hearing. They minimize the number of hits required to represent each frame of audio material at a fixed distortion level. The dynamic dictionary greatly reduces statistical redundancies in the audio source. Experiments indicate that the proposed adaptive wavelet selection procedure by itself can achieve almost transparent coding of monophonic compact disk (CD) quality signals (sampled at 44.1 kHz) at bit rates of 64-70 kilobits per second (kb/s). The combined adaptive wavelet selection and dynamic dictionary coding procedures achieve almost transparent coding of monophonic CD quality signals at bit rates of 48-66 kh/s.

A challenge of image communication over unreliable channels is to achieve good compression rates and be efficient in presence of channel failures. In this work we use Multiple Description Coding (MDC) techniques based on Wavelet Transforms, that have been shown to be powerful against channel failures. We propose a bit allocation algorithm that takes account of channel information when dispatching redundancy between descriptors. This algorithm compresses to a target bit rate with a bounded side distortion. channel 2 Scan Based DWT

Multiple Description Coding (MDC) has proven to be a powerful tool for joint source/channel coding applications. Indeed, MDC offers the possibility of controlling easily the amount of redundancy introduced in the transmitted signal while maintaining good quality decoding even when the channel is noiseless. However, to our knowledge, few work have been dedicated to the tuning of the redundancy parameter according to the channel noise level. Moreover, in case of non stationary channel a solution must be found to adapt automatically the amount of redundancy in order to maintain transmission quality. In this paper, we propose a MDC method that estimates the amount of source redundancy that must be dispatched between the different descriptors according to the channel state. This method includes a wavelet transform and an optimal bit allocation process of the binary ressources across the different descriptors and the different wavelet subbands. It takes into account the knowledge of the channel impulse response which is time variable and reflects accurately the propagation conditions encountered in a real environment. We focus on radio frequency wireless transmission. The proposed method is well suited for wideband mobile communications where the channel can be modeled as a superposition of a discrete number of paths. Simulations of the proposed MDC for different number of descriptions and redundancies are performed giving very encouraging results compared with other state-of-the-art MDC.

In this paper, we consider the bit rate maximizing problem and power minimizing problem with integer bit allocation. We will derive the duality between these two problems. We will show that if a transceiver is optimal for the powerminimizing problem, it is also optimal for the rate maximizing problem, and the converse is true. For the power minimization problem with integer bit allocation, the solution has been found in the literature. However, there is no solution yet for the rate maximization problem with integer bit allocation. The duality allows us to develop an algorithm for finding the rate-maximizing transceiver with integer bit allocation using the solution of power-minimizing system. In the simulations, we will compute the optimal solution for the rate-maximizing problem using the proposed algorithm. bit rate with integer bit constraint has not been solved. In the literature, bit rate and power are two commonly used optimalitycriteria forthe transceiverdesign. When there is...

In this paper, we jointly consider statistical precoding and feedback of bit allocation (BA) for multiple-inputmultiple-ouput (MIMO) systems over correlated channels. The proposed system will be termed a BA system. We assume that the statistics of the channel is known to the transmitter and a reverse link of very low rate is available so that the receiver can send back the quantized BA. Based on the statistics of the channel, we derive the statistical precoder so that bounds of the error rate averaged over the random correlated channel are minimized. Due to statistical precoding, the distribution of the BA is highly nonuniform. Treating BA as a vector signal, we quantize it using vector quantization (VQ), which is known to be particularly useful for quantizing signals with nonuniform distributions. As the distribution of BA is taken into consideration in the codebook design, a good tradeoff between performance and feedback rate can be achieved. Simulations show that the combination of statistical precoding and VQ-based quantization for BA leads to good performance with a small number of feedback bits.

The current paper is concerned with an effective method to quantize a spectrum envelope of a speech signal without having an inter-frame prediction. In this paper, we proposed a method referred to as dynamic bit allocation-split vector quantization (DBA-SVQ). The main feature of this structure is that it makes use of the ordering property of line spectral frequencies (LSF) and exploits multiple codebooks, normalization and the DBA technique. As a result, we can limit the dynamic range of LSF sub-vectors and allocate different numbers of bits in accordance with the range sizes to maximize the overall efficiency of quantization. The performance is compared with delta line spectral pairs (LSP) VQ, which is used in EVRC-B, demonstrating reduction in spectral distortion (SD).

Assuming the availability of the channel state information at the transmitter (CSIT) and receiver (CSIR), we consider the joint optimal transceiver design for multi-input multi-output (MIMO) communication systems. Using the geometric mean decomposition (GMD), we propose a transceiver design that can decompose, in a strictly capacity lossless manner, a MIMO channel into multiple subchannels with identical capacities. This uniform channel decomposition (UCD) scheme has two implementation forms. One is the combination of a linear precoder and a minimum mean-squared-error VBLAST (MMSE-VBLAST) detector, which is referred to as UCD-VBLAST, and the other includes a dirty paper (DP) precoder and a linear equalizer followed by a DP decoder, which we refer to as UCD-DP. The UCD scheme can provide much convenience for the modulation/demodulation and coding/decoding procedures due to obviating the need of bit allocation. We also show that UCD can achieve the maximal diversity gain. The simulation results show that the UCD scheme exhibits excellent performance even without the use of any error correcting codes.

In the design of low-bit-rate (LBR) speech coding algorithms, language variability is often considered to be of secondary importance in comparison with other operational factors such as speaker variability and noise. Given that languages dier extensively in the composition of the spectral envelope and that the quantised spectral envelope of speech represents an important part of the bit allocation in speech coding, it is surprising to ®nd that no comprehensive studies have ever been carried out on the role of language in spectral quantisation. This paper addresses this through a series of performance studies of spectral quantisation carried out across a set of language families typical of global mobile telecommunications. The study considers factors of quantiser design such as the size and structure of codebooks, and the quantity of monolingual data used in codebook training. This study found that quantisation distortion is not uniform across languages. It is shown that a signi®cant dierence exists in the behaviour of spectral quantisation across languages, in particular the behaviour of high distortion outliers. Detailed analysis of the spectral distortion data on a phonetic level revealed that the nature of the distribution of spectral energy in phonemes in¯uenced the behaviour of monolingual codebooks. Some explanations for codebook performance are presented as well as a set of recommendations for codebook design for multilingual environments.

This paper investigates the performance of split Vector Quantisation (VQ) of Line Spectral Frequencies (LSFs) across a set of 10 modem languages. Spectral quantisation accounts for a significant portion of the bit allocation in low-rate speech coding. Split VQ of LSFs can achieve transparent quantisation of the Linear Prediction Coefficients at 24 bitsleame. In this work, codebooks are trained on individual languages and the crosslanguage VQ performance was measured using Spectral Distortion (SD). The results show that the spectral structure of the codebook training language influences the perfonnance of the VQ. The number of bits/frame required for transp,arent speech varied by as much a 2 bits across languages.

Computer modeling programs that generate threedimensional (3-D) data on fine grids are capable of generating very large amounts of information. These data sets, as well as 3-D sensor/measured data sets, are prime candidates for the application of data compression algorithms. A very flexible and powerful compression algorithm for imagery data is the newly released JPEG 2000 standard. JPEG 2000 also has the capability to compress volumetric data, as described in Part 2 of the standard, by treating the 3-D data as separate slices. As a decoder standard, JPEG 2000 does not describe any specific method to allocate bits among the separate slices. This paper proposes two new bit allocation algorithms for accomplishing this task. The first procedure is rate distortion optimal (for mean squared error), and is conceptually similar to postcompression rate distortion optimization used for coding codeblocks within JPEG 2000. The disadvantage of this approach is its high computational complexity. The second bit allocation algorithm, here called the mixed model (MM) approach, mathematically models each slice's rate distortion curve using two distinct regions to get more accurate modeling at low bit rates. These two bit allocation algorithms are applied to a 3-D Meteorological data set. Test results show that the MM approach gives distortion results that are nearly identical to the optimal approach, while significantly reducing computational complexity.

This paper proposes a strategy to deal with bit rate allocation for the optimization of Maximum Absolute Error (MAE) or l-infinity distortion metric in 3-D data compression using JPEG2000. Part 2 of this standard has the capability to compress 3-D data by treating data as separate 2-D slices; these slices could be taken directly from the data or from the data after it has undergone a decorrelation transform (KLT) in one direction. To perform bit rate allocation we use a Mixed Model approximation to the MAE rate-distortion curve, that is used in an optimization algorithm. To solve the problem of MAE-related bit rate allocation in the KLT domain, we theoretically derive an upper bound for MAE based on the basis vectors of the KLT; we also develop an algorithm for optimizing this upper bound, and we illustrate how the minimization of this upper bound can decrease the actual MAE. * This work was supported by a grant from the Texas Instruments Foundation. We would like to thank Dr. Bryan Usevitch for his collaboration on related work which inspired this research. We also would like to thank A. Aguirre for many valuable software implementations. † Ed Vidal thanks PD IMETS for support of this research.