Region adaptive subband image coding

We present a region adaptive subband image coding scheme using the statistical properties of image subbands for various subband decompositions. Motivated by analytical results obtained when the input signal to the subband decomposition is a unit step function, we analyze the energy packing properties toward the lower frequency subbands, edges, and the dependency of energy distribution on the orientation of the edges, in subband decomposed images. Based on these investigations and ideal analysis/synthesis filtering done in the frequency domain, the region adaptive subband image coding scheme extracts suitably shaped regions in each subband and then uses adaptive entropy-constrained quantizers for different regions under the assumption of a generalized Gaussian distribution for the image subbands. We also address the problem of determining an optimal subband decomposition among all possible decompositions. Experimental results show that visual degradations in the reconstructed image are negligible at a bit rate of 1.0 b/pel and reasonable quality images are obtainable at rates as low as 0.25 b/pel.     

Adaptive entropy coded subband coding of images

The authors describe a design approach, called 2-D entropy-constrained subband coding (ECSBC), based upon recently developed 2-D entropy-constrained vector quantization (ECVQ) schemes. The output indexes of the embedded quantizers are further compressed by use of noiseless entropy coding schemes, such as Huffman or arithmetic codes, resulting in variable-rate outputs. Depending upon the specific configurations of the ECVQ and the ECPVQ over the subbands, many different types of SBC schemes can be derived within the generic 2-D ECSBC framework. Among these, the authors concentrate on three representative types of 2-D ECSBC schemes and provide relative performance evaluations. They also describe an adaptive buffer instrumented version of 2-D ECSBC, called 2-D ECSBC/AEC, for use with fixed-rate channels which completely eliminates buffer overflow/underflow problems. This adaptive scheme achieves performance quite close to the corresponding ideal 2-D ECSBC system.     

Fixed distortion subband coding of images for packet-switchednetworks

A subband image codec is presented that approximately attains a user-prescribed fidelity by allowing the encoder's compression rate to vary. The fixed distortion subband coding (FDSBC) system is suitable for use with future of packet-switched networks. The codec's design is based on an algorithm that allocates distortion among the subbands to minimize channel entropy. By coupling this allocation procedure with judiciously selected subband quantizers, an elementary four-band codec was obtained. Additional four-band structures may be nested in a hierarchical configuration for improved performance. Each of the configurations tested attains mean square distortions within 2.0 dB of the user-specific value over a wide range of distortion for several standard test images. Rate versus mean-square distortion performance rivals that of fixed-rate systems having similar complexity. The encoder's output is formatted to take advantage of prioritized packet networks. Simulations show that FDSBC is robust with respect to packet loss and may be used effectively for progressive transmission applications     

An integrated framework for adaptive subband image coding

Previous work on filter banks and related expansions has revealed an interesting insight: different filter bank trees can be regarded as different ways of constructing orthonormal bases for linear signal expansion. In particular, fast algorithms for finding best bases in an operational rate-distortion (R/D) sense have been successfully used in image coding. Independently of this work, other research has also explored the design of filter banks that optimize energy compaction for a single signal or a class of signals. In this paper, we integrate these two different but complementary approaches to best-basis design and propose a coding paradigm in which subband filters, tree structure, and quantizers are chosen to optimize the R/D performance. These coder attributes represent side information. They are selected from a codebook designed off-line from training data, using R/D as the design criterion. This approach provides a rational framework in which to explore alternatives to empirical design of filter banks, quantizers, and other coding parameters. The on-line coding algorithm is a relatively simple extension of current R/D-optimal coding algorithms that operate with fixed filter banks and empirically designed quantizer codebooks. In particular, it is shown that selection of the best adapted filter bank from the codebook is computationally elementary     

New prediction schemes for lossless coding of fullband and subband images

This paper presents a study of lossless image compression of fullband and subband images using predictive coding. The performance of a number of different fixed and adaptive predictors are evaluated to establish the relative performance of different predictors at various resolutions and to give an indication of the achievable image resolution for given bit rates. In particular, the median adaptive predictor is compared with two new classes of predictors proposed in this paper. One is based on the weighted median filter, while the other uses context modelling to select the optimum from a set of predictors. A graphical tool is also proposed to analyse the prediction methods. Simulations of the different predictors for a variety of real world and medical images, evaluated both numerically and graphically, show the superiority of median based prediction over this proposed implementation of context model based prediction, for all resolutions. The effects of different subband decomposition techniques are also explored.     

Regularized subband coding scheme

Two enhanced subband coding schemes using a regularized image restoration technique are proposed: the first controls the global regularity of the decompressed image; the second extends the first approach at each decomposition level. The quantization scheme incorporates scalar quantization (SQ) and pyramidal lattice vector quantization (VQ) with both optimal bit and quantizer allocation. Experimental results show that both the block effect due to VQ and the quantization noise are significantly reduced.     

基于子带金字塔结构的彩色图像小波编码

本文改进了分层树集分割算法(SPIHT),重新设计了一种子带金字塔的数据结构来组织图像的二维小波变换系数,既减少了存储空间又加快了编码速度.在彩色图像的YUV空间按位平面的顺序依次对YUV三个分量编码,输出颜色分量完全嵌入式的码流.实验结果表明改进后算法对彩色图像的编码能获得很好的率失真性能,而且适用于高分辨率、不规则图像的编解码.     

Rate-distortion-constrained subband video coding

This paper introduces a subband video coding algorithm for operation over a continuum of rates from very low to very high. The key elements of the system are statistical rate-distortion-constrained motion estimation and compensation, multistage residual quantization, high order statistical modeling, and arithmetic coding. The method is unique in that it provides an improved mechanism for dynamic spatial and temporal coding. Motion vectors are determined in a nontraditional way, using a rate-distortion cost criterion. This results in a smoother and more consistent motion field, relative to that produced by conventional block matching algorithms. Control over the system computational complexity and performance may be exercised easily     

Three-dimensional subband coding of video

We describe and show the results of video coding based on a three-dimensional (3-D) spatio-temporal subband decomposition. The results include a 1-Mbps coder based on a new adaptive differential pulse code modulation scheme (ADPCM) and adaptive bit allocation. This rate is useful for video storage on CD-ROM. Coding results are also shown for a 384-kbps rate that are based on ADPCM for the lowest frequency band and a new form of vector quantization (geometric vector quantization (GVQ)) for the data in the higher frequency bands. GVQ takes advantage of the inherent structure and sparseness of the data in the higher bands. Results are also shown for a 128-kbps coder that is based on an unbalanced tree-structured vector quantizer (UTSVQ) for the lowest frequency band and GVQ for the higher frequency bands. The results are competitive with traditional video coding techniques and provide the motivation for investigating the 3-D subband framework for different coding schemes and various applications.     

New directions in subband coding

Two very different subband coders are described. The first is a modified dynamic bit-allocation-subband coder (D-SBC) designed for variable rate coding situations and easily adaptable to noisy channel environments. It can operate at rates as low as 12 kb/s and still give good quality speech. The second coder is a 16-kb/s waveform coder, based on a combination of subband coding and vector quantization (VQ-SBC). The key feature of this coder is its short coding delay, which makes it suitable for real-time communication networks. The speech quality of both coders has been enhanced by adaptive postfiltering. The coders have been implemented on a single AT&T DSP32 signal processor     

Rate-distortion-optimal subband coding withoutperfect-reconstruction constraints

We investigate the design of subband coders without the traditional perfect-reconstruction constraint on the filters. The coder uses scalar quantizers, and its filters and bit allocation are designed to optimize a rate-distortion criterion. Using convexity analysis, we show that optimality can be achieved using filterbanks that are the cascade of a (paraunitary) principal component filterbank for the input spectral process and a set of pre and postfilters surrounding each quantizer. Analytical expressions for the pre and postfilters are then derived. An algorithm for computing the globally optimal filters and bit allocation is given. We also develop closed-form solutions for the special case of two-channel coders under an exponential rate-distortion model. Finally, we investigate a constrained-length version of the filter design problem, which is applicable to practical coding scenarios. While the optimal filterbanks are nearly perfect-reconstruction at high rates, we demonstrate an apparently surprising advantage of optimal FIR filterbanks; they significantly outperform optimal perfect-reconstruction FIR filterbanks at all bit rates     

Minimum mean-squared error transform coding and subband coding

Knowledge of the power spectrum of a stationary random sequence can be used for quantizing the signal efficiently and with minimum mean-squared error. A multichannel filter is used to transform the random sequence into an intermediate set of variables that are quantized using independent scalar quantizers, and then inverse-filtered, producing a quantized version of the original sequence. Equal word-length and optimal word-length quantization at high bit rates is considered. An analytical solution for the filter that minimizes the mean-squared quantization error is obtained in terms of its singular value decomposition. The performance is characterized by a set of invariants termed second-order modes, which are derived from the eigenvalue decomposition of the matrix-valued power spectrum. A more general rank-reduced model is used for decreasing distortion by introducing bias. The results are specialized to the case when the vector-valued time series is obtained from a scalar random sequence, which gives rise to a filter bank model for quantization. The asymptotic performance of such a subband coder is derived and shown to coincide with the asymptotic bound for transform coding. Quantization employing a single scalar pre- and postfilter, traditional transform coding using a square linear transformation, and subband coding in filter banks, arise as special cases of the structure analyzed here     

Wavelet packets and spatial adaptive intraband coding of images

In this work, we present a coding scheme based on a rate-distortion optimum wavelet packets decomposition and on an adaptive coding procedure that exploits spatial non-stationarity within each subband. We show, by means of a generalization of the concept of coding gain to the case of non-stationary signals, that it may be convenient to perform subband decomposition optimization in conjunction with intraband optimal bit allocation. In our implementation, each subband is partitioned into blocks of coefficients that are coded using a geometric vector quantizer with a rate determined on the basis of spatially local statistical characteristics. The proposed scheme appears to be simpler than other wavelet packets-based schemes presented in the literature and achieves good results in terms of both compression and visual quality.     

Shape adaptive wavelet transform for magnetic resonance images coding

Region-based coding is an important feature in today's image coding techniques as it follows different regions of the image that will be encoded at different bit rates and hence at different qualities rather than encoding the entire image with a single quality constraints. This article proposes an algorithm for the region-based coding of the brain magnetic resonance images in which the brain part will be encoded with more number of bits than the background. This method employs Shape Adaptive Discrete Wavelet Transform, which can transform the regions of interest and the background on the images independently and the coefficients can be encoded by using the SPIHT coding at different levels. This algorithm was compared with the existing wavelet-based coding techniques and a better PSNR was achieved for the same bit rate by reconstructing the region of interest with high quality than the background.     

Image data compression using subband coding

A general reversive subband coding system with 2-D infinite impulse response filters is proposed. The system considered guarantees perfect image reconstruction (free of phase distortions). Application of wave digital filters is considered. A new technique of high-frequency source encoding is proposed. The experiments with real images prove high efficiency of the technique proposed.     

Three-dimensional subband coding with motion compensation

Three-dimensional (3-D) frequency coding is an alternative approach to hybrid coding concepts used in today's standards. The first part of this paper presents a study on concepts for temporal-axis frequency decomposition along the motion trajectory in video sequences. It is shown that, if a two-band split is used, it is possible to overcome the problem of spatial inhomogeneity in the motion vector field (MVF), which occurs at the positions of uncovered and covered areas. In these cases, original pixel values from one frame are placed into the lowpass-band signal, while displaced-frame-difference values are embedded into the highpass band. This technique is applicable with arbitrary MVF's; examples with block-matching and interpolative motion compensation are given. Derivations are first performed for the example of two-tap quadrature mirror filters (QMF's), and then generalized to any linear-phase QMF's. With two-band analysis and synthesis stages arranged as cascade structures, higher resolution frequency decompositions are realizable. In the second part of the paper, encoding of the temporal-axis subband signals is discussed. A parallel filterbank scheme was used for spatial subband decomposition, and adaptive lattice vector quantization was employed to approach the entropy rate of the 3-D subband samples. Coding results suggest that high-motion video sequences can be encoded at significantly lower rates than those achievable with conventional hybrid coders. Main advantages are the high energy compaction capability and the nonrecursive decoder structure. In the conclusion, the scheme is interpreted more generally, viewed as a motion-compensated short-time spectral analysis of video sequences, which can adapt to the quickness of changes. Although a 3-D multiresolution representation of the picture information is produced, a true multiresolution representation of motion information, based on spatio-temporal decimation and interpolation of the MVF, is regarded as the still-missing part.     

Adaptive entropy-coded subband coding of image sequences

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

Multirate 3-D subband coding of video

We propose a full color video compression strategy, based on 3-D subband coding with camera pan compensation, to generate a single embedded bit stream supporting multiple decoder display formats and a wide, finely gradated range of bit rates. An experimental implementation of our algorithm produces a single bit stream, from which suitable subsets are extracted to be compatible with many decoder frame sizes and frame rates and to satisfy transmission bandwidth constraints ranging from several tens of kilobits per second to several megabits per second. Reconstructed video quality from any of these bit stream subsets is often found to exceed that obtained from an MPEG-1 implementation, operated with equivalent bit rate constraints, in both perceptual quality and mean squared error. In addition, when restricted to 2-D, the algorithm produces some of the best results available in still image compression.     

Motion-compensated 3-D subband coding of video

This paper describes a video coding system based on motion-compensated three-dimensional (3-D) subband/wavelet coding (MC-3DSBC), which can overcome the limits of both 3-D SBC and MC prediction-based coding. In this new system, spatio-temporal subbands are generated by MC temporal analysis and a spatial wavelet transform, and then encoded by 3-D subband-finite state scalar quantization (3DSB-FSSQ). The rate allocation from the GOP level to each class of subbands is optimized by utilizing the structural property of MC-3DSBC that additive superposition approximately holds for both rate and distortion. The proposed video coding system is applied to several test video clips. Its performance exceeds that of both a known MPEG-1 implementation and a similar subband MC predictive coder while maintaining modest computational complexity and memory size.     

On the adaptive three-dimensional transform coding techniques for moving images

In this paper, an adaptive three-dimensional transform coding technique based on the 3-D discrete cosine transform (DCT) for removing the temporal correlation is proposed. Because of the nonstationary nature of the image data, the energy distribution in a 3-D DCT block varies along the vertical, horizontal and temporal directions. Thus, adaptive schemes, such as the 3-D classification, the classified linear scanning technique and the VLC table selection scheme, are used to take local variations into account. Also, in our approach, a hybrid technique, which adaptively combines relatively simple inter-frame coding with intra-frame coding, is presented. Through intensive computer simulations, the performance of the proposed 3-D transform coding technique is evaluated on several well-known moving sequences. The results show that, especially for moving sequences containing slow or moderate motion, the proposed technique provides an improved performance over the scheme with motion compensation (CCITT, 1989) at rates above 0.5 b/pixel (bpp), and a good visual quality of the reconstructed images is also obtained. Thus, the proposed 3-D transform coding technique is believed to be a good candidate for the digital VCR, since motion compensation is not required in the proposed 3-D coding technique.