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RECURSIVE BLOCK coding - A NEW APPROACH TO transform coding

IEEE TRANSACTIONS ON COMMUNICATIONS 1986年第2期34卷 161-179页

作者： FARRELLE, PM JAIN, AK Signal and Image Processing Laboratory Department of Electrical and Computer Engineering University of California Davis CA USA

The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields has been extended to higher order autoregressive (AR) sequences and practical images yielding what we call recursive block coding (RBC) algorithms. In general, the rate-distortion performance for these algorithms is significantly superior to that of the conventional block KL transform algorithm. Moreover, these algorithms permit the use of small size transforms, thereby removing the need for fast transforms and making the hardware implementation of such coders more appealing. This improved performance has been verified for practical image data and results in suppression of the block-boundary effect commonly observed in traditional transform coding techniques. This is illustrated by comparing RBC with cosine transform coding using both one- and twodimensional algorithms. Examples of RBC encoded images at various rates are given.

关键词： transform coding Karhunen-Loeve transforms Block codes Data compression Image coding Signal processing Image processing Bit rate Markov processes Rate-distortion

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LLIC: Large Receptive Field transform coding With Adaptive Weights for Learned Image Compression

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IEEE TRANSACTIONS ON MULTIMEDIA 2024年 26卷 10937-10951页

作者： Jiang, Wei Ning, Peirong Yang, Jiayu Zhai, Yongqi Gao, Feng Wang, Ronggang Peking Univ Sch Elect & Comp Engn Shenzhen 518055 Peoples R China Peng Cheng Lab Shenzhen 518000 Peoples R China

The effective receptive field (ERF) plays an important role in transform coding, which determines how much redundancy can be removed during transform and how many spatial priors can be utilized to synthesize textures during inverse transform. Existing methods rely on stacks of small kernels, whose ERFs remain insufficiently large, or heavy non-local attention mechanisms, which limit the potential of high-resolution image coding. To tackle this issue, we propose Large Receptive Field transform coding with Adaptive Weights for Learned Image Compression (LLIC). Specifically, for the first time in the learned image compression community, we introduce a few large kernel-based depth-wise convolutions to reduce more redundancy while maintaining modest complexity. Due to the wide range of image diversity, we further propose a mechanism to augment convolution adaptability through the self-conditioned generation of weights. The large kernels cooperate with non-linear embedding and gate mechanisms for better expressiveness and lighter point-wise interactions. Our investigation extends to refined training methods that unlock the full potential of these large kernels. Moreover, to promote more dynamic inter-channel interactions, we introduce an adaptive channel-wise bit allocation strategy that autonomously generates channel importance factors in a self-conditioned manner. To demonstrate the effectiveness of the proposed transform coding, we align the entropy model to compare with existing transform methods and obtain models LLIC-STF, LLIC-ELIC, and LLIC-TCM. Extensive experiments demonstrate that our proposed LLIC models have significant improvements over the corresponding baselines and reduce the BD-Rate by 9.49%,9.47%,and10.94% on Kodak over VTM-17.0 Intra, respectively. Our LLIC models achieve state-of-the-art performances and better trade-offs between performance and complexity.

关键词： Image coding transforms transform coding Kernel Complexity theory Entropy Convolutional codes Learned image compression

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A new class of biorthogonal wavelet systems for image transform coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1998年第7期7卷 1000-1013页

作者： Wei, D Tian, J Wells, RO Burrus, CS Rice Univ Dept Elect & Comp Engn Houston TX 77251 USA Rice Univ Dept Math Houston TX 77251 USA

We construct general biorthogonal Coifman wavelet systems, a new class of compactly supported biorthogonal wavelet systems with vanishing moments equally distributed for a scaling function and wavelet pair, A time-domain design method is employed and closed-form expressions for the impulse responses and the frequency responses of the corresponding dual filters are derived, The resulting filter coefficients are all dyadic fractions, which is an attractive feature in the realization of multiplication-free discrete wavelet transform, Even-ordered systems in this family are symmetric, which correspond to linear-phase dual filters, In particular, three filterbanks (FB's) in this family are systematically verified to have competitive compression potential to the 9-7 tap biorthogonal wavelet FB by Cohen et al., which is currently the most widely used one in the field of wavelet transform coding. In addition, the proposed FB's have much smaller computational complexity in terms of floating-point operations required in transformation, and therefore indicate a better tradeoff between compression performance and computational complexity.

关键词： image coding source coding transform coding wavelet transforms

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Human Motion Capture Data Tailored transform coding

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2015年第7期21卷 848-859页

作者： Hou, Junhui Chau, Lap-Pui Magnenat-Thalmann, Nadia He, Ying Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Nanyang Technol Univ Inst Media Innovat Singapore 639798 Singapore Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

Human motion capture (mocap) is a widely used technique for digitalizing human movements. With growing usage, compressing mocap data has received increasing attention, since compact data size enables efficient storage and transmission. Our analysis shows that mocap data have some unique characteristics that distinguish themselves from images and videos. Therefore, directly borrowing image or video compression techniques, such as discrete cosine transform, does not work well. In this paper, we propose a novel mocap-tailored transform coding algorithm that takes advantage of these features. Our algorithm segments the input mocap sequences into clips, which are represented in 2D matrices. Then it computes a set of data-dependent orthogonal bases to transform the matrices to frequency domain, in which the transform coefficients have significantly less dependency. Finally, the compression is obtained by entropy coding of the quantized coefficients and the bases. Our method has low computational cost and can be easily extended to compress mocap databases. It also requires neither training nor complicated parameter setting. Experimental results demonstrate that the proposed scheme significantly outperforms state-of-the-art algorithms in terms of compression performance and speed.

关键词： Motion capture transform coding data compression optimization

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ADAPTIVE BLOCK transform coding OF SPEECH BASED ON LPC VECTOR QUANTIZATION

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1991年第12期39卷 2611-2620页

作者： HUSSAIN, Y FARVARDIN, N UNIV MARYLAND SYST RES CTR COLLEGE PK MD 20742 USA

In this paper we describe several adaptive block transform speech coding systems based on vector quantization of LPC parameters. In order to account for the power fluctuations, the speech signal is normalized to have a unit-energy prediction residual. The temporal variations in the short-term spectrum, on the other hand, are taken into account by vector quantizing the LPC parameters associated with the vector of speech samples and transmitting the codeword index. Also, a variation of the scheme in which the pitch information is used to better estimate the spectrum is considered. For each block, based on the codevector associated with the input vector, an optimum bit assignment map is used to quantize the transform coefficients. We consider two types of zero-memory quantizers for encoding the transform coefficients, namely the Lloyd-Max quantizer and the entropy-coded quantizer. The performance of these schemes is compared with other adaptive transform coding schemes. We show by means of simulations that the system based on entropy-coded quantizer design leads to very high performance and in most cases as much as 5-dB performance improvement in terms of segmental signal-to-noise ratio is observed over the adaptive block transform coding scheme of Zelinski and Noll. The effect of incorporating the pitch information in the coder is studied and numerical results are presented. The effects of the bit rate and the size of the codebook on the performance of the systems are also studied in detail.

关键词： transform coding Speech coding Linear predictive coding Vector quantization Bit rate Hidden Markov models State estimation Encoding Signal design Signal to noise ratio

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Performance analysis of hierarchical transform coding with a large kernel for video codecs

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IET IMAGE PROCESSING 2014年第1期8卷 12-22页

作者： Lee, Bumshik Kim, Munchurl Kim, Hui Yong Choi, Jin Soo Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA Korea Adv Inst Sci & Technol Dept Elect Engn Taejon 305701 South Korea Elect & Telecommun Res Inst Div Broadcasting Media Taejon 305700 South Korea

In this study, the performance of hierarchical transform coding is analysed with design of an order-16 integer transform kernel. The proposed hierarchical transform-coding structure is constructed with a set of 4 x 4, 8 x 8 and 16 x 16 integer transforms of variable transform block sizes, which takes the advantages of both lower and higher transform kernels by flexibly adapting to varying image characteristics of video sequences with homogeneous and complex regions. The proposed hierarchical transform-coding structure is implemented as an extension to H.264/advanced video coding joint model. The authors show the effectiveness of the hierarchical variable-sized block transform scheme by analysing the quantisation effects and the correlation among neighbouring pixels in video sequences of different spatial resolutions. The experimental results show that: (i) the variable-sized block transform scheme with the hierarchical structure is advantageous to the texture regions with strong local edges and (ii) the higher-order-16 integer transform kernel itself is more effective for the homogeneous texture regions, which are often encountered in higher resolution sequences. Therefore these two features can complementarily work in an rate-distortion (RD) optimised manner for various characteristics of the input signals.

关键词： correlation methods image resolution image sequences quantisation (signal) transform coding video codecs order-16 integer transform kernel large kernel coding variable-sized block transform scheme spatial resolutions correlation quantisation effects video sequences image characteristics variable transform block sizes video codecs hierarchical transform coding performance analysis

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Improved image decompression for reduced transform coding artifacts

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1995年第6期5卷 490-499页

作者： ORourke, TP Stevenson, RL Laboratory for Image and Signal Analysis Department of Electrical Engineering University of Notre Dame Notre Dame IN USA

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data, Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which remits in a reconstructed image that best fits a non-Gaussian Markov random held (MRF) image model. This approach results in a convex constrained optimization problem that can be solved iteratively, At each iteration, the gradient projection method is used to update the estimate based on the image model, In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform, The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

关键词： transform coding Image reconstruction Quantization Image coding Bit rate Degradation Stochastic processes Markov random fields Constraint optimization Discrete cosine transforms

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Canonical coordinates for transform coding of noisy sources

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2006年第1期54卷 235-243页

作者： Schreier, PJ Scharf, LL Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW Australia Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA Colorado State Univ Dept Stat Ft Collins CO 80523 USA

Based on the additive white quantization noise model, linear transform coders are derived for Gaussian sources corrupted by noise. There are two alternative design objectives: minimizing the trace of the error correlation matrix and thus minimizing the mean-squared error, or minimizing the determinant of the error correlation matrix and thus maximizing information rate. It is shown that a solution to both problems is to first transform the noisy observations into canonical coordinates, quantize and apply a Wiener filter in this coordinate system, and then transform the result back to the original coordinates. Canonical coordinates are uncorrelated, and quantization and Wiener filtering are applied to each component independently. The type of canonical coordinate system depends on the design objective: Quantization in half-canonical coordinates minimizes the mean-squared error and quantization in full-canonical coordinates maximizes information rate. Finally, it is also demonstrated in this paper that majorization is the fundamental principle underlying proofs of optimal transform coding.

关键词： canonical coordinates majorization quantization rank reduction transform coding

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Minimum mean-squared error transform coding and subband coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 1996年第4期42卷 1179-1192页

作者： Aas, KC Mullis, CT Electrical and Computer Engineering University of Colorado Boulder CO USA

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.

关键词： quantization transform coding subband coding filter bank rank reduction algebra of multichannel linear systems

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HIGH-QUALITY AUDIO transform coding AT 64-KBPS

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IEEE TRANSACTIONS ON COMMUNICATIONS 1994年第11期42卷 3010-3019页

作者： MAHIEUX, Y PETIT, JP Centre National d''Etudes Des Telecommunications Lannion France

This paper presents a transform coding algorithm devoted to high quality audio coding at a bit rate of 64 kbps per monophonic channel. It enables the transmission of a high quality stereo sound through the basic access (2B channels) of ISDN. Although a complete system including framing, synchronization and error correction has been developed, only the bit rate compression algorithm is described here. A detailed analysis of the signal processing techniques such as the time/frequency transformation, the pre-echo reduction by adaptive filtering, the fast algorithm computations, etc., is provided. The use of psychoacoustical properties is also precisely reported. Finally, some subjective evaluation results and one real time implementation of the coder using the ATT DSP32C digital signal processor are presented.

关键词： transform coding Signal processing algorithms Bit rate Audio coding ISDN Frequency synchronization Error correction Compression algorithms Signal analysis Algorithm design and analysis

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