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.     

Optimised frequency-domain bit allocation for video coding

An optimal frequency domain bit allocation technique is presented. A Lagrange multiplier based approach is used for the rate-distortion optimisation of a quantisation matrix in video coding. Since the optimal quantisation matrix is heavily dependent on the choice of quantiser, the quantiser is also jointly optimised in order to alleviate the interaction between the two. The complexity of the algorithm is analysed, and it is shown to be directly proportional to the number of possible quantisation matrices and quantisation scales. Experimental results comparing the new technique with a conventional video encoder are also presented.     

Side-match tree-structured vector quantiser for image progressive coding

The balanced tree-structured vector quantiser is the traditional method of achieving image progressive coding. During image progressive coding, an image is decoded step-by-step in a decoder. The author proposes an unbalanced tree-structured vector quantiser to perform image progressive coding for a given series of rate thresholds. Side-match vector quantisation and its variants have been proposed to reduce the bit rate in image coding. The tree-structured vector quantiser and the side-match vector quantiser are combined to perform image progressive coding, achieving a better coding quality than that obtained using only the tree-structured vector quantiser at the same bit rate.     

Adaptive compression of medical ultrasound images

An adaptive image-coding algorithm for compression of medical ultrasound (US) images in the wavelet domain is presented. First, it is shown that the histograms of wavelet coefficients of the subbands in the US images are heavy-tailed and can be better modelled by using the generalised Student's t-distribution. Then, by exploiting these statistics, an adaptive image coder named JTQVS-WV is designed, which unifies the two approaches to image-adaptive coding: rate-distortion (R-D) optimised quantiser selection and R-D optimal thresholding, and is based on the varying-slope quantisation strategy. The use of varying-slope quantisation strategy (instead of fixed R-D slope) allows coding of the wavelet coefficients across various scales according to their importance for the quality of reconstructed image. The experimental results show that the varying-slope quantisation strategy leads to a significant improvement in the compression performance of the JTQVS-WV over the best state-of-the-art image coder, SPIHT, JPEG2000 and the fixed-slope variant of JTQVS-WV named JTQ-WV. For example, the coding of US images at 0.5 bpp yields a peak signal-to-noise ratio gain of >0.6, 3.86 and 0.3 dB over the benchmark, SPIHT, JPEG2000 and JTQ-WV, respectively.     

Importance of quantiser design compared to optimal multigrid motionestimation in video coding

Adaptive flow computation and DCT quantisation play complementary roles in motion compensated video coding schemes. Since the introduction of the intuitive entropy-constrained motion estimation of Dufaux et al. (1995), several optimal variable-size block matching algorithms have been proposed. Many of these approaches put forward their intrinsic optimality, but the corresponding visual effect has not been explored. The relative importance of optimal multigrid motion estimation with regard to quantisation is addressed in the context of MPEG-like coding. It is shown that while simpler (suboptimal) motion estimates give subjective results as good as the optimal motion estimates, small enhancements in the quantiser have significant visual effects. This suggests that more attention should be paid to the quantiser design     

Adaptive vector quantisation of non-orthogonal representations for image compression

An efficient compression technique employing adaptive vector quantisation of multiple non-orthogonal transform domain representations of still images is developed. For each sub-image, the encoder selects a code from the domain that yields best representation. The performance improvement employing the proposed technique relative to existing single domain vector quantisation coding methods, for the same compression ratio, is obtained at the expense of increased computational complexity.     

Image compression using improved hybrid classified vector quantisation

A novel image compression technique using classified vector quantiser and singular value decomposition is proposed for the efficient representation of still images. The proposed method is called improved hybrid classified vector quantisation. The proposed technique was benchmarked with the standard vector quantiser generated using the k-means algorithm, and JPEG-2000. Simulation results indicate that the proposed approach alleviates edge degradation and can reconstruct good visual quality images with higher peak signal-to-noise ratio than the benchmarked techniques     

Low bit-rate video coding using wavelet vector quantisation

A method for low bit-rate video coding based on wavelet vector quantisation is proposed. Motion estimation/compensation using overlapped block matching (OBM) is employed to eliminate the blocking effects in the prediction error introduced by conventional block matching. It is shown that OBM significantly increases the efficiency of the wavelet transform coder. The motion-compensated interframe prediction error is decomposed using a wavelet transform and a method is employed for the efficient coding of the wavelet coefficients. In this technique, the coefficients are coded with a zero-tree multistage lattice vector quantiser. Simulation results are provided to evaluate the coding performance of the described coding scheme for low bit-rate video coding. It provides constant bit rate, obviating the need for buffer, with just small fluctuations in PSNR. Moreover, comparison with the RM8 implementation of the standard H261 video coder shows that the presented codec provides improvements in both peak signal-to-noise ratio and picture quality     

Adaptive lossless coding scheme of lattice vector quantisation

In the process of quantisation, a lattice vector quantiser (LVQ) generates radius and index sequences. In lossless coding, the radius sequence is run-length coded and then Huffman or arithmetic coded, and the index sequence is represented by fixed binary bits. The author has improved the LVQ lossless coding by removing the redundant information between radius sequence and index sequence. An algorithm is developed that redistributes radius and index sequences. The algorithm adaptively shifts down large indices to smaller values and reduces the index bits. Hence, the proposed LVQ lossless coding method reduces the gap between actual coding bit rates and the optimal bit rate boundary. For a Laplacian source the proposed lossless coding scheme achieves more than 10% of bit reduction at bit rates higher than 0.7 bits/sample over the traditional lossless coding method     

Partial-distortion-weighted fuzzy competitive learning algorithmfor vector quantisation

An effective competitive learning algorithm called the partial-distortion-weighted fuzzy competitive learning (PDW-FCL) algorithm is developed for vector quantisation. The PDW-FCL algorithm is able to minimise the likelihood of neuron (codevector) underuse and make good use of every neuron for optimal vector quantiser design     

A method for the assessment of the performance of high-speed analogue/digital convertors

A method is proposed for the measurement of the accuracy of high-speed analogue/digital convertors, using automatic digital counting of the occupancy of each quantisation level by a known input signal. The results provide a dynamic quantisation characteristic and can be related to specific quantiser defects.     

Image sequence coding using adaptive vector quantisation in wavelet transform domain

A new scheme for image sequence coding using the wavelet transform and adaptive vector quantisation is proposed. The transform is used to decompose an image into multiresolution and multiband sub-images. Adaptive vector quantisation is then applied to achieve image data compression with good quality and low bit rate. Experimental results are presented.<>     

Novel scheme for low-power classified vector quantisation imagecoding

A novel scheme for low-power image coding and decoding based on classified vector quantisation is presented. The main idea is the replacement of the memory accesses to large background memories (most power-consuming operations), by arithmetic and/or application-specific computations. Specifically, the proposed image coding scheme uses small sub-codebooks to reduce the memory requirements and memory-related power consumption in comparison with classical vector quantisation schemes. By applying simple transformations on the codewords during coding, the proposed scheme extends the small sub-codebooks, compensating for the quality degradation introduced by their small size. Thus, the main coding task becomes computation-based rather than memory-based, leading to a significant reduction in power consumption. The proposed scheme achieves image qualities comparable with, or better than, those of traditional vector quantisation schemes, as the parameters of the transformations depend on the image block under coding, and the small sub-codebooks are dynamically adapted each time to this specific image block. The main disadvantage of the proposed scheme is the decrease in the compression ratio in comparison with classical vector quantisation. A joint (quality-compression ratio) optimisation procedure is used to keep this side-effect as small as possible     

Optimal quantisation strategy for DCT image compression

The authors present a strategy for generating optimal quantisation tables for use in JPEG image compression and its extension to general block sizes. Directly optimised quantisation tables were obtained by simulated annealing. A composite cost function minimised the RMS error between original and recovered images while keeping the compression ratio close to some desired value. Examination of these tables led to a simple model giving quantisation coefficients in terms of (x, y) position in the table and three model parameters. Annealing on the model parameters for several compressions yielded an expression for each parameter as a function of compression ratio. This approach was extended to general block sizes, and psychovisual evaluation determined the visually optimal block size for each compression ratio. The authors demonstrate significant improvements over JPEG coding due to the use of optimal quantisation rather than default tables. Use of general block size effectively extends the JPEG approach to higher compressions than are feasible with standard JPEG coding     

Smooth side-match weighted vector quantiser with variable block size for image coding

Although side-match vector quantisation (SMVQ) reduces the bit rate, the quality of image coding using SMVQ generally degenerates as the grey level transition across the boundaries of neighbouring blocks increases or decreases. The author proposes a smooth side-match weighted method to yield a state codebook according to the smoothness of the grey levels between neighbouring blocks. When a block is encoded, a corresponding weight is assigned to each neighbouring block to represent its relative importance. This smooth side-match weighted vector quantisation (SSMWVQ) achieves a higher PSNR than SMVQ at the same bit rate. Also, each block can be pre-encoded in an image, allowing each encoded block to use all neighbouring blocks to yield the state codebook in SSMWVQ, rather than using only two neighbouring blocks, as in SMVQ. Moreover, SSMWVQ selects many high-detail blocks as basic blocks to enhance the coding quality, and merges many low-detail blocks into a larger one to reduce further the bit rate. Experimental results reveal that SSMWVQ has a higher PSNR and lower bit rate than other methods.     

Asymptotic stabilisation of system with finite-level logarithmic quantiser

A quantised feedback control for the asymptotic stabilisation of a system with a finite-level logarithmic quantiser is proposed. The main idea is to employ one from among the current, upper and lower quantising levels as the quantised input to maintain the decreasing property of a Lyapunov function. The resulting controller allows for an arbitrarily small quantisation density, whereas existing controllers in the literature do not, in the finite-level logarithmic quantiser for asymptotic stabilisation.     

High compression vector quantisation scheme for image coding

An address-predicted vector quantiser (APVQ) is proposed for image coding, which exploits correlation among intervectors by means of predicting. Compared with the general vector quantiser, the APVQ can obtain higher compression ratio, while keeping the same picture quality.<>     

Fast image colourisation based on twin-codebook vector quantisation

A novel colourisation scheme for grey-level images based on twincodebook vector quantisation (TBVQ) is presented. Different from the traditional vector quantiser with the same codebook in the encoding and decoding processes, the proposed TBVQ adopts two different but related codebooks in the encoder and decoder, respectively. During the colourisation process, the target image is first encoded by the greyscale codebook and then decoded by the related chromatic codebook. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm.     

Adaptive error coding using channel prediction

In this paper, we construct a finite-state Markov chain model for a Rayleigh fading channel by partitioning the range of the received signal envelope into K intervals. Using a simulation of the classic two-ray Rayleigh fading model, a Markov transition probability matrix is obtained. Using this matrix to predict the channel state, we introduce an adaptive forward error correction (FEC) coding scheme. Simulation results are presented to show that the adaptive FEC coding scheme significantly improves the performance of a wireless communication system.     

Combined source-channel coding using turbo-codes

The authors present a new approach to combined source-channel coding based on using the reliability information available from the turbo-code channel decoder. Numerical results are presented for the transmission of the DCT coefficients of still images showing a noticeable improvement with respect to an ordinary, as well as a channel optimised quantiser