Digital signal processing (DSP) covers a wide range of applications such as signal acquisition, analysis, transmission, storage, and synthesis. Special attention is needed for the VLSI (very large scale integration) implementation of high performance DSP systems with examples from video and radar applications. This book provides basic architectures for VLSI implementations of DSP tasks covering architectures for application specific circuits and programmable DSP circuits. It fills an important gap in the literature by focusing on the transition from algorithms specification to architectures for VLSI implementations. Areas covered include:

• architectures for basic operations and elementary functions
• parallel processing and pipelining
• application specific array processors
• programmable digital signal processors

This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.

This text explains how advances in wavelet analysis provide new means for multiresolution analysis and describes its wide array of powerful tools. The book covers such topics as: the variations of the windowed Fourier transform; constructions of special waveforms suitable for specific tasks; the use of redundant representations in reconstruction and enhancement; applications of efficient numerical compression as a tool for fast numerical analysis; and approximation properties of various waveforms in different contexts.

Robust Technology with Analysis of Interference in Signal Processing discusses for the first time the theoretical fundamentals and algorithms of analysis of noise as an information carrier. On their basis the robust technology of noisy signals processing is developed. This technology can be applied to solving the problems of control, identification, diagnostics, and pattern recognition in petrochemistry, energetics, geophysics, medicine, physics, aviation, and other sciences and industries. The text explores the emergent possibility of forecasting failures on various objects, in conjunction with the fact that failures follow the hidden microchanges revealed via interference estimates. This monograph is of interest to students, postgraduates, engineers, scientific associates and others who are concerned with the processing of measuring information on computers.

This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.

Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation.

Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques.

Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.

Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.

Due to the rapid increase in readily available computing power, a corre sponding increase in the complexity of problems being tackled has occurred in the field of systems as a whole. A plethora of new methods which can be used on the problems has also arisen with a constant desire to deal with more and more difficult applications. Unfortunately by increasing the ac curacy in models employed along with the use of appropriate algorithms with related features, the resultant necessary computations can often be of very high dimension. This brings with it a whole new breed of problem which has come to be known as "The Curse of Dimensionality" . The expression "Curse of Dimensionality" can be in fact traced back to Richard Bellman in the 1960's. However, it is only in the last few years that it has taken on a widespread practical significance although the term di mensionality does not have a unique precise meaning and is being used in a slightly different way in the context of algorithmic and stochastic complex ity theory or in every day engineering. In principle the dimensionality of a problem depends on three factors: on the engineering system (subject), on the concrete task to be solved and on the available resources. A system is of high dimension if it contains a lot of elements/variables and/or the rela tionship/connection between the elements/variables is complicated."

This text is the first published survey of recent research in signal processing for music transcription, edited and authored by authorities in the field. It covers a range of topics, from the structure and decomposition of signals, pitch and multipitch estimation, coding methods for sound separation, automatic sound source identification and sequence transcription, to using computational modeling and neural networks for music transcription. The book targets a growing audience interested in MPEG-7 standardization. It is a reference for researchers and students in signal processing, computer science, acoustics and music.

Spectacular advances during the last decade have altered the related disciplines of computing and telecommunications beyond all recognition. The developments in the"enabling technologies,"which have made these advances possible, have been less obvious to the casual observer. The subject of this book is one of these technologies--the coding of still images and picture sequences (video).
Digital Compression of Still Images and Video is general in approach and covers all the recognized coding algorithms; explaining their basic theory in enough detail that the reader will understand the principles involved. Results which have been achieved with coding algorithms by researchers in all parts of the world are also discussed. A brief historical review of the area is included to orient those new to the field, and the work is supported by references spanning the period from the earliest work on time/frequency analysis, to the latest topic of research interest--image sequence transmission using asynchronous transfer mode (ATM) techniques.
This book will make an excellent reference for graduates and researchers working on image coding and transmission, and will also be of use to those in the related areas of computer vision and multimedia developments. It is essential reading for the rapidly increasing number of technical and professional staff in the industrial environment who, maybe for the first time, are coming to grips with image coding.
Key Features
* Provides complete and up-to-date coverage of all digital image and video coding (compression) techniques
* Includes more than 850 references covering relevant work from the 1940s to the present
* Presents information on new directions in coding
* Contains details on current coding standards
* Describes and explains all algorithms in use for image coding

The rapid advancements in image communication technologies are documented in the book series, Advances in Image Communication. Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive overview of the whole.

This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between these two steps and the whole compression process is discussed.

The five chapters specifically present the theory of wavelets applied to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed. Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms; a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given). The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.

Image communication technologies have advanced rapidly in recent years and the book series, Advances in Image Communication is dedicated to documenting these developments. Third in the series, this publication contributes as effectively as its forerunners to the multidisciplinary overview afforded by the series as a whole. At the same time, it stands alone as a comprehensive synopsis of its own particular area of interest.

The book specifically explores two complementary topics, namely:

the coding algorithms made to compress the data rate of digital moving-picture sequences (video-telephony, television TV] and high-definition television HDTV]) and

the transmission on Asynchronous Transfer Mode ATM] networks (packet-switching transmission media). It provides an in-depth view of the current state-of-the-art and endeavors to stimulate increasing research efforts for the future.

Signal processing applications have burgeoned in the past decade. During the same time, signal processing techniques have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This trend will continue as many new signal processing applications are opening up in consumer products and communications systems.
In particular, signal processing has been making increasingly sophisticated use of linear algebra on both theoretical and algorithmic fronts. This volume gives particular emphasis to exposing broader contexts of the signal processing problems so that the impact of algorithms and hardware can be better understood; it brings together the writings of signal processing engineers, computer engineers, and applied linear algebraists in an exchange of problems, theories, and techniques. This volume will be of interest to both applied mathematicians and engineers.

This book brings together papers presented at the 2016 International Conference on Communications, Signal Processing, and Systems, which provides a venue to disseminate the latest developments and to discuss the interactions and links between these multidisciplinary fields. Spanning topics ranging from communications to signal processing and systems, this book is aimed at undergraduate and graduate students in electrical engineering, computer science and mathematics, researchers and engineers from academia and industry as well as government employees (such as NSF, DOD and DOE).

The design and construction of three-dimensional 3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.

The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.

A smart camera is an integrated machine vision system which, in addition to image capture circuitry, includes a processor, which can extract information from images without need for an external processing unit, and interface devices used to make results available to other devices. This book provides content on smart cameras for an interdisciplinary audience of professionals and students in embedded systems, image processing, and camera technology. It serves as a self-contained, single-source reference for material otherwise found only in sources such as conference proceedings, journal articles, or product data sheets. Coverage includes the 50 year chronology of smart cameras, their technical evolution, the state-of-the art, and numerous applications, such as surveillance and monitoring, robotics, and transportation.

The area of adaptive systems, which encompasses recursive identification, adaptive control, filtering, and signal processing, has been one of the most active areas of the past decade. Since adaptive controllers are fundamentally nonlinear controllers which are applied to nominally linear, possibly stochastic and time-varying systems, their theoretical analysis is usually very difficult. Nevertheless, over the past decade much fundamental progress has been made on some key questions concerning their stability, convergence, performance, and robustness. Moreover, adaptive controllers have been successfully employed in numerous practical applications, and have even entered the marketplace.

Multimedia Signals and Systems is an essential text for professional and academic researchers and students in the field of multimedia.
Multimedia Signals and Systems is primarily a technical introductory level multimedia textbook, including problems, examples, and MATLABA(R) codes. It will be a stepping-stone for readers who want to research in audio processing, image and video processing, and data compression.
This book will also be useful to readers who are carrying out research and development in systems areas such as television engineering and storage media.
Anyone who seeks to learn the core multimedia signal processing techniques and systems will need Multimedia Signals and Systems. There are many chapters that are generic in nature and provide key concepts of multimedia systems to technical as well as non-technical persons.
There are also several chapters that provide a mathematical/ analytical framework for basic multimedia signal processing. The readers are expected to have some prior knowledge about discrete signals and systems, such as Fourier transform and digital filters. However, a brief review of these theories is provided.
The accompanying CD provides several MATLABA(R) codes along with a few test data samples; e.g., audio, image and video.
Multimedia Signals and Systems is suitable for advanced-level courses in multimedia and is also a well-needed addition to the professional reference library in this area.

Audio and speech processing have achieved important status in development in the last three decades, improving the standard of living of many people. Regarding these applications, several signal processing algorithms have been developed to assist the speech impaired and improve the learning ability of children. Advances in Audio and Speech Signal Processing: Technologies and Applications provides a comprehensive approach of signal processing tools regarding the enhancement, recognition, and protection of speech and audio signals. Advances in Audio and Speech Signal Processing: Technologies and Applications offers researchers and practitioners the information they need to develop and implement efficient signal processing algorithms in the enhancement field.

This book presents models and procedures to design pipeline analog-to-digital converters, compensating for device inaccuracies, so that high-performance specs can be met within short design cycles. These models are capable of capturing and predicting the behavior of pipeline data converters within less than half-a-bit deviation, versus transistor-level simulations. As a result, far fewer model iterations are required across the design cycle. Models described in this book accurately predict transient behaviors, which are key to the performance of discrete-time systems and hence to the performance of pipeline data converters.

Signal Measurement and Estimation Techniques for Micro and Nanotechnology discusses micro, nano and robotic cells and gives a state-of-the-art presentation of the different techniques and solutions to measure and estimate signals at the micro and nano scale. New technologies and applications such as micromanipulation (artificial components, biological objects), micro-assembly (MEMS, MOEMS, NEMS) and material and surface force characterization are covered. The importance of sensing at the micro and nano scale is presented as a key issue in control systems, as well as for understanding the physical phenomena of these systems. The book also:
Explains issues that make signal measurement and estimation techniques difficult at the micro-nano-scale and offers solutions
Discusses automated micro-assembly, and control of micro-nano roboticdevices
Presents and links signal measurement and estimation techniques for micro-nano scale systems with microfabrication methods, sensors integration and control schemes
Signal Measurement and Estimation Techniques for Micro and Nanotechnology is a must-read for researchers and engineers working in MEMS and control systems."

Essential background reading for engineers and scientists working in such fields as communications, control, signal, and image processing, radar and sonar, radio astronomy, seismology, remote sensing, and instrumentation. The book can be used as a textbook for a single course, as well as a combination of an introductory and an advanced course, or even for two separate courses, one in signal detection, the other in estimation.

Learn how and when to apply the latest phase and phase-difference modulation (PDM) techniques with this valuable guide for systems engineers and researchers. It helps you cut design time and fine-tune system performance.

A key element of any modern video codec is the efficient exploitation of temporal redundancy via motion-compensated prediction. In this book, a novel paradigm of representing and employing motion information in a video compression system is described that has several advantages over existing approaches. Traditionally, motion is estimated, modelled, and coded as a vector field at the target frame it predicts. While this "prediction-centric" approach is convenient, the fact that the motion is "attached" to a specific target frame implies that it cannot easily be re-purposed to predict or synthesize other frames, which severely hampers temporal scalability. In light of this, the present book explores the possibility of anchoring motion at reference frames instead. Key to the success of the proposed "reference-based" anchoring schemes is high quality motion inference, which is enabled by the use of a more "physical" motion representation than the traditionally employed "block" motion fields. The resulting compression system can support computationally efficient, high-quality temporal motion inference, which requires half as many coded motion fields as conventional codecs. Furthermore, "features" beyond compressibility - including high scalability, accessibility, and "intrinsic" framerate upsampling - can be seamlessly supported. These features are becoming ever more relevant as the way video is consumed continues shifting from the traditional broadcast scenario to interactive browsing of video content over heterogeneous networks. This book is of interest to researchers and professionals working in multimedia signal processing, in particular those who are interested in next-generation video compression. Two comprehensive background chapters on scalable video compression and temporal frame interpolation make the book accessible for students and newcomers to the field.

The fields of image analysis, computer vision, and artificial intelligence all make use of descriptions of shape in grey-level images. Most existing algorithms for the automatic recognition and classification of particular shapes have been devel oped for specific purposes, with the result that these methods are often restricted in their application. The use of advanced and theoretically well-founded math ematical methods should lead to the construction of robust shape descriptors having more general application. Shape description can be regarded as a meeting point of vision research, mathematics, computing science, and the application fields of image analy sis, computer vision, and artificial intelligence. The NATO Advanced Research Workshop "Shape in Picture" was organised with a twofold objective: first, it should provide all participants with an overview of relevant developments in these different disciplines; second, it should stimulate researchers to exchange original results and ideas across the boundaries of these disciplines. This book comprises a widely drawn selection of papers presented at the workshop, and many contributions have been revised to reflect further progress in the field. The focus of this collection is on mathematical approaches to the construction of shape descriptions from grey-level images. The book is divided into five parts, each devoted to a different discipline. Each part contains papers that have tutorial sections; these are intended to assist the reader in becoming acquainted with the variety of approaches to the problem."