Multistage Vector Quantization Research Articles

Comparison between adaptive search and bit allocation algorithms for image compression using vector quantization

This article discusses bit allocation and adaptive search algorithms for mean-residual vector quantization (MRVQ) and multistage vector quantization (MSVQ). The adaptive search algorithm uses a buffer and a distortion threshold function to control the bit rate that is assigned to each input vector. It achieves a constant rate for the entire image but variable bit rate for each vector in the image. For a given codebook and several bit rates, we compare the performance between the optimal bit allocation and adaptive search algorithms. The results show that the performance of the adaptive search algorithm is only 0.20-0.53 dB worse than that of the optimal bit allocation algorithm, but the complexity of the adaptive search algorithm is much less than that of the optimal bit allocation algorithm.

Subband coding with multistage VQ for wireless image communication

A subband multistage vector quantization (SB-MSVQ) coding technique is proposed for wireless image communication. The Digital European Cordless Telecommunications (DECT) system has been used as a wireless communication environment. The impact of channel fading on the SB-MSVQ coding technique is investigated and its performance is compared with that of the baseline JPEG standard. Simulation results show that the proposed technique, SB-MSVQ, is very robust to channel fading errors even at a very low channel power, whereas the baseline JPEG suffers from channel fading errors which are visually very annoying. Due to the inherent structure of SB-MSVQ, the important low frequency information of an image is packed into a small portion of the encoded data. If this portion is received intact by the SB-MSVQ decoder, the overall quality degradation of the reconstructed image is marginal.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Multi-stage hierarchical address vector quantization for image coding

Abstract A new vector quantization (VQ) scheme for encoding images is presented. The proposed scheme is called multi-stage hierarchical address vector quantization and it combines the concepts of multi-stage VQ (MSVQ), hierarchical VQ (HVQ) and address VQ (AVQ). Its encoder consists of several stages where the HVQ or AVQ is applied while the larger image blocks are divided into smaller sub-blocks. Digital decimation and interpolation techniques are used to reduce the blocking efTect in the reconstructed images. Experimental results show thai the proposed coding scheme performs better than HVQ, MSVQ, AVQ, multi-layer address VQ and memoryless VQ systems.

Tree-structured residual vector quantisation with constrained storage for image coding

A tree-structured residual vector quantisation (VQ) algorithm with constrained storage based on a codebook sharing algorithm is proposed. The algorithm provides an intermediate property of multistage VQ and tree-structured VQ, and thereby can trade off coding performance for storage requirement. The algorithm is especially suited to image coding where a large vector dimension is preferred due to its coding efficiency. >

Wavelet transform image coding using lattice vector quantisation

A novel method for the efficient coding of image wavelet coefficients using zerotree multistage lattice vector quantisation is presented. This method achieves high compression ratios with good picture quality, maintaining a very simple implementation. Simulation results demonstrate that the coding performance of this algorithm favourably compares to some of the best reported image compression results.

A fast searching technique for multistage residual vector quantizers

The encoding procedure for multistage residual vector quantizers consists of searching a tree to find the codeword that best matches the input. Many techniques have been proposed for searching such trees, ranging from the slow and faithful to the fast and inaccurate. The present authors introduce a simple method, which they call dynamic M-search, that is both fast and effective for searching the residual vector quantization tree. The new method is applied to image coding, performance results are presented, and advantages are shown over conventional M-search. >

Generalized Product Code Vector Quantization: A Family of Efficient Techniques for Signal Compression

Under the constraint of limited complexity, structured vector quantization (VQ) can outperform unstructured VQ. We show that a large family of structured VQ schemes are special cases of a generalized product code (GPC) model. In this model, an input vector is (a) decomposed by the encoder into multiple feature vectors that are sequentially encoded, where the choice of codebook for a particular feature depends on how the prior feature was encoded, and (b) reproduced by the decoder from a synthesis operation on the quantized feature vectors. Many existing VQ structures and audio and visual signal compression schemes can be advantageously studied, extended, and designed from the perspective of this model. We present design methods for GPCs, including: (i) algorithms that allow a controlled trade-off between reproduction fidelity (or distortion) and encoding or storage complexity; (ii) an algorithm paradigm for joint optimization of multiple codebooks. The GPC methods are illustrated with applications to summation product codes, which include the now-classical schemes of multistage VQ (MSVQ) and tree-structured VQ (TSVQ). Among the results is a procedure for designing balanced TSVQ codebooks to arbitrary depths, and MSVQ-TSVQ hybrid structures that furnish enhanced trade-offs between complexity and distortion-rate performance.

Hierarchical sub-band coding of super high definition image with adaptive block-size multistage VQ

A hierarchical image coding algorithm based on sub-band coding and adaptive block-size multistage vector quantization (VQ) is proposed, and its coding performance is examined for super high definition (SHD) image. First, the concept on SHD image is briefly described. Next, the signal power spectrum is evaluated, and the sub-band analysis pattern is determined from its characteristics. Several quadrature mirror filters are examined from the viewpoints of reconstruction accuracy, coding gain, and low-pass signal quality. Then an optimum filter is selected for the sub-band analysis. The two-stage VQ using the adaptive bit allocation is also introduced to control quantization accuracy and to achieve high-quality image reproduction. Coding performance and hierarchical image reconstruction are demonstrated using SNR and some photographs.

A unified approach to tree-structured and multistage vector quantization for noisy channels

The large encoding complexity and sensitivity to channel errors of vector quantization (VQ) are discussed. The performance of two low-complexity VQs-the tree-structured VQ (TSVQ) and the multistage VQ (MSVQ)-when used over noisy channels are analyzed. An algorithm is developed for the design of channel-matched TSVQ (CM-TSVQ) and channel-matched MSVQ (CM-MSVQ) under the squared-error criterion. Extensive numerical results are given for the correlation coefficient 0.9. Comparisons with the ordinary TSVQ and MSVQ designed for the noiseless channel show substantial improvements when the channel is very noisy. The CM-MSVQ, which can be regarded as a block-structured combined source-channel coding scheme, is compared with a block-structured tandem source-channel coding scheme (with the same block length as the CM-MSVQ). For the Gauss-Markov source, the CM-MSVQ outperforms the tandem scheme in all cases that the authors have considered. It is demonstrated that the CM-MSVQ is fairly robust to channel mismatch. >

Modular VLSI architectures for real-time full-search-based vector quantization

Vector quantization (VQ) has become feasible to be employed for real-time applications by using VLSI technology. In this paper, the authors propose modular linearly connected VLSI architectures for VQ that can support real-time image processing applications. Each processing element in the design consists of an adder and a shift register instead of a multiplier. The designs require fixed I/O bandwidth with the host and allow codebook changes. The throughput is independent of the codebook size. These designs can be extended to the case when a fixed number of processors are available. A number of VQ schemes-single-stage and multistage VQ, classified VQ, etc.-can be implemented using this approach. >

Efficient search and design procedures for robust multi-stage VQ of LPC parameters for 4 kb/s speech coding

A tree-searched multistage vector quantization (VQ) scheme for linear prediction coding (LPC) parameters which achieves spectral distortion lower than 1 dB with low complexity and good robustness using rates as low as 22 b/frame is presented. The M-L search is used, and it is shown that it achieves performance close to that of the optimal search for a relatively small M. A joint codebook design strategy for multistage VQ which improves convergence speed and the VQ performance measures is presented. The best performance/complexity tradeoffs are obtained with relatively small size codebooks cascaded in a 3-6 stage configuration. It is shown experimentally that as the number of stages is increased above the optimal performance/complexity tradeoff, the quantizer robustness and outlier performance can be improved at the expense of a slight increase in rate. Results for log area ratio (LAR) and line spectral pairs (LSPs) parameters are presented. A training technique that reduces outliers at the expense of a slight average performance degradation is introduced. The method significantly outperforms the split codebook approach.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Unrestricted multistage vector quantizers

A low-complexity, high-performance vector quantization technique for medium-to-high-bit-rate encoding based on multistage (residual) VQ is introduced. The design, a variable-rate version of multistage VQ, is the vector extension of the piecewise uniform scalar quantizers of P.F. Swaszek and J.B. Thomas (1984), and is related to the piecewise uniform VQs of F. Kuhlmann and J.A. Buckview (1988). Examples for the independent Gaussian and Laplacian sources are included. >

Enhanced multistage vector quantization by joint codebook design

Multistage vector quantization (MSVQ) can achieve very low encoding and storage complexity in comparison to unstructured vector quantization. However, the conventional stage-by-stage design of the codebooks in MSVQ is suboptimal with respect to the overall performance measure. The authors introduce an algorithm for the joint design of the stage codebooks to optimize the overall performance. The performance improvement, although modest, is achieved with no effect on encoding or storage complexity and only a slight increase in design effort.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

New multistage scheme for vector quantisation of parcor coefficients

A new multistage scheme for vector quantisation of PARCOR coefficients for low bit rate speech coding is proposed. The novelty of this scheme is that the lattice filter structure is preserved after the quantisation. This is achieved by coupling the forward and backward prediction errors across vector quantisation (VQ) stages. Simulation results show that the new scheme can achieve lower average distortion than other multistage VQ schemes.

Block transform image coding by multistage vector quantization with optimal bit allocation

A multistage vector quantization with optimal bit allocation (MVQ-OBA) in the transform domain is presented. A set of bit allocation planes is first obtained by slicing a (scalar) optimal bit allocation map where the number of bits assigned to each coefficient is proportional to the coefficient variance. The set of bit allocation planes determines the coefficients to be used and the codebook size at each stage. The vector dimensionalities are restricted to small values and relatively small codebooks are used, thus reducing both the overhead required for transmitting the codebooks and the complexity in codebook design. The computer simulation results demonstrate that MVQ-OBA is competitive with many other transform coding techniques including variable length transform coding. MVQ-OBA is well suited for progressive transmission. >

Constrained-storage quantization of multiple vector sources by codebook sharing

A codebook sharing technique, called constrained storage vector quantization (CSVQ), is introduced. This technique offers a convenient and optimal way of trading off performance against storage. The technique can be used in conjunction with tree-structured vector quantization (VQ) and other structured VQ techniques that alleviate the search complexity obstacle. The effectiveness of CSVQ is illustrated for coding transform coefficients of audio signals with multistage VQ. >

Bit-serial VLSI implementation of vector quantizer for real-time image coding

A practical high-throughput architecture and its implementation for real-time coding of television-quality signals are presented. The architecture is directed toward the implementation of multistage vector quantization (VQ), as the authors' simulation results show that the latter is more suitable for real-time coding. However, the implementation is suitable for both single-stage and multistage VQ. The functional blocks of the VQ encoder system have been designed and implemented in VLSI technology. The VQ encoding scheme designed has an encoding delay of 25 clock cycles and is independent of the codebook size.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Picture coding by an adaptive multistage vector quantization

AbstractAn adaptive multistage vector quantizing system is proposed for highly efficient picture coding method and its coding performances are investigated. This system contains a multistage vector quantizer which means that comparatively large picture blocks are quantized first, then the remaining quantization error is quantized in smaller blocks, gradually refining the resolution at subsequent stages. That is, a rough picture is coded first and finer structures are coded later. Computer simulation studies on several picture samples demonstrate the excellent processing efficiency of the proposed method in comparison with conventional vector quantizers.

Dynamic multistage vector quantization of images

AbstractThe research and development of low bit‐rate high‐efficiency coding methods for teleconferencing are progressing in many directions. In the recent paper, dynamic multistage vector quantization is proposed to reduce both temporal and spatial redundancy of motion pictures. First, a dynamic vector quantization algorithm is proposed exploiting the correlation due to the almost periodic nature of the input signal. In addition, the clustering process of the motion vector is investigated in relation to dynamic codebook generation. Next, based on statistical properties of the residual image signal, an adaptive vector quantization with mean separation and normalization is described, and a multistage structure is introduced. The computer simulation results relating to the proposed dynamic multistage vector quantizer show about 37 dB SN ratio at 0.15 ‐ 0.2 bit/pixel for actual motion images.

Shape adaptive activity controlled multistage gain shape vector quantisation of images

The performance of a shape adaptive activity controlled multistage gain shape vector quantiser for digital image compression is compared with that of more established full search multistage vector quantisation methods. The advantages of the former approach to the vector quantisation coding of images are clearly demonstrated via computer simulation of the respective coding algorithms.