608 research outputs found
Role of anticausal inverses in multirate filter-banks. I. System-theoretic fundamentals
In a maximally decimated filter bank with identical decimation ratios for all channels, the perfect reconstructibility property and the nature of reconstruction filters (causality, stability, FIR property, and so on) depend on the properties of the polyphase matrix. Various properties and capabilities of the filter bank depend on the properties of the polyphase matrix as well as the nature of its inverse. In this paper we undertake a study of the types of inverses and characterize them according to their system theoretic properties (i.e., properties of state-space descriptions, McMillan degree, degree of determinant, and so forth). We find in particular that causal polyphase matrices with anticausal inverses have an important role in filter bank theory. We study their properties both for the FIR and IIR cases. Techniques for implementing anticausal IIR inverses based on state space descriptions are outlined. It is found that causal FIR matrices with anticausal FIR inverses (cafacafi) have a key role in the characterization of FIR filter banks. In a companion paper, these results are applied for the factorization of biorthogonal FIR filter banks, and a generalization of the lapped orthogonal transform called the biorthogonal lapped transform (BOLT) developed
Compression methods for mechanical vibration signals: Application to the plane engines
International audienceA novel approach for the compression of mechanical vibration signals is presented in this paper. The method relies on a simple and flexible decomposition into a large number of subbands, implemented by an orthogonal transform. Compression is achieved by a uniform adaptive quantization of each subband. The method is tested on a large number of real vibration signals issued by plane engines. High compression ratios can be achieved, while keeping a good quality of the reconstructed signal. It is also shown that compression has little impact on the detection of some commonly encountered defects of the plane engine
Advanced Telecommunications and Signal Processing Program
Contains an introduction and reports on eleven research projects.Advanced Telecommunications Research Progra
Attractor image coding with low blocking effects.
by Ho, Hau Lai.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 97-103).Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Overview of Attractor Image Coding --- p.2Chapter 1.2 --- Scope of Thesis --- p.3Chapter 2 --- Fundamentals of Attractor Coding --- p.6Chapter 2.1 --- Notations --- p.6Chapter 2.2 --- Mathematical Preliminaries --- p.7Chapter 2.3 --- Partitioned Iterated Function Systems --- p.10Chapter 2.3.1 --- Mathematical Formulation of the PIFS --- p.12Chapter 2.4 --- Attractor Coding using the PIFS --- p.16Chapter 2.4.1 --- Quadtree Partitioning --- p.18Chapter 2.4.2 --- Inclusion of an Orthogonalization Operator --- p.19Chapter 2.5 --- Coding Examples --- p.21Chapter 2.5.1 --- Evaluation Criterion --- p.22Chapter 2.5.2 --- Experimental Settings --- p.22Chapter 2.5.3 --- Results and Discussions --- p.23Chapter 2.6 --- Summary --- p.25Chapter 3 --- Attractor Coding with Adjacent Block Parameter Estimations --- p.27Chapter 3.1 --- δ-Minimum Edge Difference --- p.29Chapter 3.1.1 --- Definition --- p.29Chapter 3.1.2 --- Theoretical Analysis --- p.31Chapter 3.2 --- Adjacent Block Parameter Estimation Scheme --- p.33Chapter 3.2.1 --- Joint Optimization --- p.34Chapter 3.2.2 --- Predictive Coding --- p.36Chapter 3.3 --- Algorithmic Descriptions of the Proposed Scheme --- p.39Chapter 3.4 --- Experimental Results --- p.40Chapter 3.5 --- Summary --- p.50Chapter 4 --- Attractor Coding using Lapped Partitioned Iterated Function Sys- tems --- p.51Chapter 4.1 --- Lapped Partitioned Iterated Function Systems --- p.53Chapter 4.1.1 --- Weighting Operator --- p.54Chapter 4.1.2 --- Mathematical Formulation of the LPIFS --- p.57Chapter 4.2 --- Attractor Coding using the LPIFS --- p.62Chapter 4.2.1 --- Choice of Weighting Operator --- p.64Chapter 4.2.2 --- Range Block Preprocessing --- p.69Chapter 4.2.3 --- Decoder Convergence Analysis --- p.73Chapter 4.3 --- Local Domain Block Searching --- p.74Chapter 4.3.1 --- Theoretical Foundation --- p.75Chapter 4.3.2 --- Local Block Searching Algorithm --- p.77Chapter 4.4 --- Experimental Results --- p.79Chapter 4.5 --- Summary --- p.90Chapter 5 --- Conclusion --- p.91Chapter 5.1 --- Original Contributions --- p.91Chapter 5.2 --- Subjects for Future Research --- p.92Chapter A --- Fundamental Definitions --- p.94Chapter B --- Appendix B --- p.96Bibliography --- p.9
Contributions in image and video coding
Orientador: Max Henrique Machado CostaTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia ElĂ©trica e de ComputaçãoResumo: A comunidade de codificação de imagens e vĂdeo vem tambĂ©m trabalhando em inovações que vĂŁo alĂ©m das tradicionais tĂ©cnicas de codificação de imagens e vĂdeo. Este trabalho Ă© um conjunto de contribuições a vários tĂłpicos que tĂŞm recebido crescente interesse de pesquisadores na comunidade, nominalmente, codificação escalável, codificação de baixa complexidade para dispositivos mĂłveis, codificação de vĂdeo de mĂşltiplas vistas e codificação adaptativa em tempo real. A primeira contribuição estuda o desempenho de trĂŞs transformadas 3-D rápidas por blocos em um codificador de vĂdeo de baixa complexidade. O codificador recebeu o nome de Fast Embedded Video Codec (FEVC). Novos mĂ©todos de implementação e ordens de varredura sĂŁo propostos para as transformadas. Os coeficiente 3-D sĂŁo codificados por planos de bits pelos codificadores de entropia, produzindo um fluxo de bits (bitstream) de saĂda totalmente embutida. Todas as implementações sĂŁo feitas usando arquitetura com aritmĂ©tica inteira de 16 bits. Somente adições e deslocamentos de bits sĂŁo necessários, o que reduz a complexidade computacional. Mesmo com essas restrições, um bom desempenho em termos de taxa de bits versus distorção pĂ´de ser obtido e os tempos de codificação sĂŁo significativamente menores (em torno de 160 vezes) quando comparados ao padrĂŁo H.264/AVC. A segunda contribuição Ă© a otimização de uma recente abordagem proposta para codificação de vĂdeo de mĂşltiplas vistas em aplicações de video-conferĂŞncia e outras aplicações do tipo "unicast" similares. O cenário alvo nessa abordagem Ă© fornecer vĂdeo com percepção real em 3-D e ponto de vista livre a boas taxas de compressĂŁo. Para atingir tal objetivo, pesos sĂŁo atribuĂdos a cada vista e mapeados em parâmetros de quantização. Neste trabalho, o mapeamento ad-hoc anteriormente proposto entre pesos e parâmetros de quantização Ă© mostrado ser quase-Ăłtimo para uma fonte Gaussiana e um mapeamento Ăłtimo Ă© derivado para fonte tĂpicas de vĂdeo. A terceira contribuição explora várias estratĂ©gias para varredura adaptativa dos coeficientes da transformada no padrĂŁo JPEG XR. A ordem de varredura original, global e adaptativa do JPEG XR Ă© comparada com os mĂ©todos de varredura localizados e hĂbridos propostos neste trabalho. Essas novas ordens nĂŁo requerem mudanças nem nos outros estágios de codificação e decodificação, nem na definição da bitstream A quarta e Ăşltima contribuição propõe uma transformada por blocos dependente do sinal. As transformadas hierárquicas usualmente exploram a informação residual entre os nĂveis no estágio da codificação de entropia, mas nĂŁo no estágio da transformada. A transformada proposta neste trabalho Ă© uma tĂ©cnica de compactação de energia que tambĂ©m explora as similaridades estruturais entre os nĂveis de resolução. A idĂ©ia central da tĂ©cnica Ă© incluir na transformada hierárquica um nĂşmero de funções de base adaptativas derivadas da resolução menor do sinal. Um codificador de imagens completo foi desenvolvido para medir o desempenho da nova transformada e os resultados obtidos sĂŁo discutidos neste trabalhoAbstract: The image and video coding community has often been working on new advances that go beyond traditional image and video architectures. This work is a set of contributions to various topics that have received increasing attention from researchers in the community, namely, scalable coding, low-complexity coding for portable devices, multiview video coding and run-time adaptive coding. The first contribution studies the performance of three fast block-based 3-D transforms in a low complexity video codec. The codec has received the name Fast Embedded Video Codec (FEVC). New implementation methods and scanning orders are proposed for the transforms. The 3-D coefficients are encoded bit-plane by bit-plane by entropy coders, producing a fully embedded output bitstream. All implementation is performed using 16-bit integer arithmetic. Only additions and bit shifts are necessary, thus lowering computational complexity. Even with these constraints, reasonable rate versus distortion performance can be achieved and the encoding time is significantly smaller (around 160 times) when compared to the H.264/AVC standard. The second contribution is the optimization of a recent approach proposed for multiview video coding in videoconferencing applications or other similar unicast-like applications. The target scenario in this approach is providing realistic 3-D video with free viewpoint video at good compression rates. To achieve such an objective, weights are computed for each view and mapped into quantization parameters. In this work, the previously proposed ad-hoc mapping between weights and quantization parameters is shown to be quasi-optimum for a Gaussian source and an optimum mapping is derived for a typical video source. The third contribution exploits several strategies for adaptive scanning of transform coefficients in the JPEG XR standard. The original global adaptive scanning order applied in JPEG XR is compared with the localized and hybrid scanning methods proposed in this work. These new orders do not require changes in either the other coding and decoding stages or in the bitstream definition. The fourth and last contribution proposes an hierarchical signal dependent block-based transform. Hierarchical transforms usually exploit the residual cross-level information at the entropy coding step, but not at the transform step. The transform proposed in this work is an energy compaction technique that can also exploit these cross-resolution-level structural similarities. The core idea of the technique is to include in the hierarchical transform a number of adaptive basis functions derived from the lower resolution of the signal. A full image codec is developed in order to measure the performance of the new transform and the obtained results are discussed in this workDoutoradoTelecomunicações e TelemáticaDoutor em Engenharia ElĂ©tric
Sparse Approximation and Dictionary Learning with Applications to Audio Signals
PhDOver-complete transforms have recently become the focus of a wide wealth of research in
signal processing, machine learning, statistics and related fields. Their great modelling
flexibility allows to find sparse representations and approximations of data that in turn
prove to be very efficient in a wide range of applications. Sparse models express signals as
linear combinations of a few basis functions called atoms taken from a so-called dictionary.
Finding the optimal dictionary from a set of training signals of a given class is the objective
of dictionary learning and the main focus of this thesis. The experimental evidence
presented here focuses on the processing of audio signals, and the role of sparse algorithms
in audio applications is accordingly highlighted.
The first main contribution of this thesis is the development of a pitch-synchronous
transform where the frame-by-frame analysis of audio data is adapted so that each frame
analysing periodic signals contains an integer number of periods. This algorithm presents
a technique for adapting transform parameters to the audio signal to be analysed, it
is shown to improve the sparsity of the representation if compared to a non pitchsynchronous
approach and further evaluated in the context of source separation by binary
masking.
A second main contribution is the development of a novel model and relative algorithm
for dictionary learning of convolved signals, where the observed variables are sparsely approximated
by the atoms contained in a convolved dictionary. An algorithm is devised to
learn the impulse response applied to the dictionary and experimental results on synthetic
data show the superior approximation performance of the proposed method compared to
a state-of-the-art dictionary learning algorithm.
Finally, a third main contribution is the development of methods for learning dictionaries
that are both well adapted to a training set of data and mutually incoherent. Two
novel algorithms namely the incoherent k-svd and the iterative projections and rotations
(ipr) algorithm are introduced and compared to different techniques published in the
literature in a sparse approximation context. The ipr algorithm in particular is shown
to outperform the benchmark techniques in learning very incoherent dictionaries while
maintaining a good signal-to-noise ratio of the representation
Theory, design and applications of linear transforms for information transmission
The aim of this dissertation is to study the common features of block transforms, subband filter banks, and wavelets, and demonstrate how discrete uncertainty can be applied to evaluate these different decomposition techniques. In particular, we derive an uncertainty bound for discrete-time functions. It is shown that this bound is the same as that for continuous-time functions, if the discrete-time functions have a certain degree of regularity.
This dissertation also deals with spectral modeling in filter banks. It is shown, both theoretically and experimentally, that subspectral modeling is superior to full spectrum modeling if performed before the rate change. The price paid for this performance improvement is an increase of computations. A few different signal sources were considered in this study. It is shown that the performances of AR and ARMA modeling techniques are comparable in subspectral modeling. The first is desired because of its simplicity. As an application of AR modeling, a coding algorithm of speech, namely CELP embedded in a filter bank structure was also studied. We found that there were no improvements of subband CELP technique over the full band one. The theoretical reasonings of the experimental results are also given.
This dissertation also addresses the problems of what type of transform to be used and to what extent an image should be decomposed. To this aim, an objective and subjective evaluations of different transform bases were done.
We propose a smart algorithm for the decomposition of a channel into its sub-channels in the discrete multitone communications. This algorithm evaluates the unevenness and energy distribution of the channel spectrum in order to get its Variable adaptive partitioning. It is shown that the proposed algorithm leads to a near optimal performance of the discrete multitone transceiver. This flexible splitting of the channel suffers less from the aliasing problem that exists in blind decompositions using fixed transforms. This dissertation extends the discrete multitone to the flexible multiband concept which brings significant performance improvements for digital communications
Digital acoustics: processing wave fields in space and time using DSP tools
Systems with hundreds of microphones for acoustic field acquisition, or hundreds of loudspeakers for rendering, have been proposed and built. To analyze, design, and apply such systems requires a framework that allows us to leverage the vast set of tools available in digital signal processing in order to achieve intuitive and efficient algorithms. We thus propose a discrete space-time framework, grounded in classical acoustics, which addresses the discrete nature of the spatial and temporal sampling. In particular, a short-space/time Fourier transform is introduced, which is the natural extension of the localized or short-time Fourier transform. Processing in this intuitive domain allows us to easily devise algorithms for beam-forming, source separation, and multi-channel compression, among other useful tasks. The essential space band-limitedness of the Fourier spectrum is also used to solve the spatial equalization task required for sound field rendering in a region of interest. Examples of applications are show
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