Direct3D 11 offers such a wealth of capabilities that users can sometimes get lost in the details of specific APIs and their implementation. While there is a great deal of low-level information available about how each API function should be used, there is little documentation that shows how best to leverage these capabilities. Written by active members of the Direct3D community, Practical Rendering and Computation with Direct3D 11 provides a deep understanding of both the high and low level concepts related to using Direct3D 11. The first part of the book presents a conceptual introduction to Direct3D 11, including an overview of the Direct3D 11 rendering and computation pipelines and how they map to the underlying hardware. It also provides a detailed look at all of the major components of the library, covering resources, pipeline details, and multithreaded rendering. Building upon this material, the second part of the text includes detailed examples of how to use Direct3D 11 in common rendering scenarios. The authors describe sample algorithms in-depth and discuss how the features of Direct3D 11 can be used to your advantage. All of the source code from the book is accessible on an actively maintained open source rendering framework. The sample applications and the framework itself can be downloaded from http://hieroglyph3.codeplex.com By analyzing when to use various tools and the tradeoffs between different implementations, this book helps you understand the best way to accomplish a given task and thereby fully leverage the potential capabilities of Direct3D 11. Key Features Presents the high level concepts used to design algorithms Describes the nuts and bolts of how to implement the algorithms Explains each of the major components of the Direct3D 11 library Shows how Direct3D 11 can be used in a variety of real-world situations Provides source code and sample programs on a supplementary website

With the ubiquitous use of digital imaging, a new profession has emerged: imaging engineering. Designed for newcomers to imaging science and engineering, Theoretical Foundations of Digital Imaging Using MATLAB (R) treats the theory of digital imaging as a specific branch of science. It covers the subject in its entirety, from image formation to image perfecting. Based on the author's 50 years of working and teaching in the field, the text first addresses the problem of converting images into digital signals that can be stored, transmitted, and processed on digital computers. It then explains how to adequately represent image transformations on computers. After presenting several examples of computational imaging, including numerical reconstruction of holograms and virtual image formation through computer-generated display holograms, the author introduces methods for image perfect resampling and building continuous image models. He also examines the fundamental problem of the optimal estimation of image parameters, such as how to localize targets in images. The book concludes with a comprehensive discussion of linear and nonlinear filtering methods for image perfecting and enhancement. Helping you master digital imaging, this book presents a unified theoretical basis for understanding and designing methods of imaging and image processing. To facilitate a deeper understanding of the major results, it offers a number of exercises supported by MATLAB programs, with the code available at www.crcpress.com.

Inspection is crucial to the management of ageing infrastructure. Visual information on structures is regularly collected but very little work exists on its organised and quantitative analysis, even though image processing can significantly enhance these inspection processes and transfer real financial and safety benefits to the managers, owners and users. Additionally, new opportunities exist in the fast evolving sectors of wind and wave energy to add value to image-based inspection techniques. This book is a first for structural engineers and inspectors who wish to harness the full potential of cameras as an inspection tool. It is particularly directed to the inspection of offshore and marine structures and the application of image-based methods in underwater inspections. It outlines a set of best practice guidelines for obtaining imagery, then the fundamentals of image processing are covered along with several image processing techniques which can be used to assess multiple damage forms: crack detection, corrosion detection, and depth analysis of marine growth on offshore structures. The book provides benchmark performance measures for these techniques under various visibility conditions using an image repository which will help inspectors to envisage the effectiveness of the techniques when applied. MATLAB (R) scripts and access to the underwater image repository are included so readers can run these techniques themselves. Practising engineers and managers of infrastructure assets are guided in image processing based inspection. Researchers can use this book as a primer, and it also suits advanced graduate courses in infrastructure management or on applied image processing.

Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach demonstrates the use of image simulation for SAR. It covers the various applications of SAR (including feature extraction, target classification, and change detection), provides a complete understanding of SAR principles, and illustrates the complete chain of a SAR operation. The book places special emphasis on a ground-based SAR, but also explains space and air-borne systems. It contains chapters on signal speckle, radar-signal models, sensor-trajectory models, SAR-image focusing, platform-motion compensation, and microwave-scattering from random media. While discussing SAR image focusing and motion compensation, it presents processing algorithms and applications that feature extraction, target classification, and change detection. It also provides samples of simulation on various scenarios, and includes simulation flowcharts and results that are detailed throughout the book. Introducing SAR imaging from a systems point of view, the author: Considers the recent development of MIMO SAR technology Includes selected GPU implementation Provides a numerical analysis of system parameters (including platforms, sensor, and image focusing, and their influence) Explores wave-target interactions, signal transmission and reception, image formation, motion compensation Covers all platform motion compensation and error analysis, and their impact on final image radiometric and geometric quality Describes a ground-based SFMCW system Principles of Synthetic Aperture Radar Imaging: A System Simulation Approach is dedicated to the use, study, and development of SAR systems. The book focuses on image formation or focusing, treats platform motion and image focusing, and is suitable for students, radar engineers, and micr

Proper analysis of image and multimedia data requires efficient extraction and segmentation techniques. Among the many computational intelligence approaches, the soft computing paradigm is best equipped with several tools and techniques that incorporate intelligent concepts and principles. This book is dedicated to object extraction, image segmentation, and edge detection using soft computing techniques with extensive real-life application to image and multimedia data. The authors start with a comprehensive tutorial on the basics of brain structure and learning, and then the key soft computing techniques, including evolutionary computation, neural networks, fuzzy sets and fuzzy logic, and rough sets. They then present seven chapters that detail the application of representative techniques to complex image processing tasks such as image recognition, lighting control, target tracking, object extraction, and edge detection. These chapters follow a structured approach with detailed explanations of the problems, solutions, results, and conclusions. This is both a standalone textbook for graduates in computer science, electrical engineering, system science, and information technology, and a reference for researchers and engineers engaged with pattern recognition, image processing, and soft computing.

The combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems in computer vision.

This authoritative text/reference presents an interdisciplinary selection of important, cutting-edge research on RGB-D based computer vision. Divided into four sections, the book opens with a detailed survey of the field, followed by a focused examination of RGB-D based 3D reconstruction, mapping and synthesis. The work continues with a section devoted to novel techniques that employ depth data for object detection, segmentation and tracking, and concludes with examples of accurate human action interpretation aided by depth sensors.

Topics and features: discusses the calibration of color and depth cameras, the reduction of noise on depth maps, and methods for capturing human performance in 3D; reviews a selection of applications which use RGB-D information to reconstruct human figures, evaluate energy consumption, and obtain accurate action classification; presents an innovative approach for 3D object retrieval, and for the reconstruction of gas flow from multiple Kinect cameras; describes an RGB-D computer vision system designed to assist the visually impaired, and another for smart-environment sensing to assist elderly and disabled people; examines the effective features that characterize static hand poses, and introduces a unified framework to enforce both temporal and spatial constraints for hand parsing; proposes a new classifier architecture for real-time hand pose recognition, and a novel hand segmentation and gesture recognition system.

Researchers and practitioners working in computer vision, HCI and machine learning will find this to be a must-read text. The book also serves as a useful reference for graduate students studying computer vision, pattern recognition or multimedia.

Architecture for the Commons dives into an analysis of how the tectonics of a building is fundamentally linked to the economic organizations that allow them to exist. By tracing the origins and promises of current technological practices in design, the book provides an alternative path, one that reconsiders the means of achieving complexity through combinatorial strategies. This move requires reconsidering serial production with crowdsourcing and user content in mind. The ideas presented will be explored through the design research developed within Plethora Project, a design practice that explores the use of video game interfaces as a mechanism for participation and user design. The research work presented throughout the book seeks to align with a larger project that is currently taking place in many different fields: The Construction of the Commons. By developing both the ideological and physical infrastructure, the project of the Commons has become an antidote to current economic practices that perpetuate inequality. The mechanisms of the production and governance of the Commons are discussed, inviting the reader to get involved and participate in the discussion. The current political and economic landscape calls for a reformulation of our current economic practices and alternative value systems that challenge the current market monopolies. This book will be of great interest not only to architects and designers studying the impact of digital technologies in the field of design but also to researchers studying novel techniques for social participation and cooperating of communities through digital networks. The book connects principles of architecture, economics and social sciences to provide alternatives to the current production trends.

Long used in undergraduate and introductory graduate courses, Astrophysical Techniques, Seventh Edition provides an accessible yet comprehensive account of the innovate instruments, detectors, and techniques employed in astronomy and astrophysics. Emphasizing the underlying unity of all astronomical observations, this popular textbook provides a coherent state-of-the-art account of the instruments and techniques used in current astronomy and astrophysics. Fully updated throughout, this seventh edition builds upon the sixth edition, covering improved techniques and cutting-edge methods in the field, as well as other exciting new developments in gravitational waves, dark matter and energy, the use of photonics, and astronomy education and outreach, in addition to further detailed discussions on the latest scientific instruments and individual detectors. The book is written in a very accessible manner, and most of the mathematics is accessible to those who have attended a mathematics course in their final years at school. Nevertheless, the treatment of the topics in general is at a sufficiently high level to be of use to those professionals seeking technical information in areas of astronomy with which they might not be completely familiar. Key Features: Details the instrumentation and theory of astronomical observations, including radio waves, gamma rays, cosmic rays, neutrinos, gravitational waves and dark matter and energy and more Presents the background theory and operating practice of state-of-the-art detectors and instruments Fully updated to contain the latest technology and research developments

Long used in undergraduate and introductory graduate courses, Astrophysical Techniques, Seventh Edition provides an accessible yet comprehensive account of the innovate instruments, detectors, and techniques employed in astronomy and astrophysics. Emphasizing the underlying unity of all astronomical observations, this popular textbook provides a coherent state-of-the-art account of the instruments and techniques used in current astronomy and astrophysics. Fully updated throughout, this seventh edition builds upon the sixth edition, covering improved techniques and cutting-edge methods in the field, as well as other exciting new developments in gravitational waves, dark matter and energy, the use of photonics, and astronomy education and outreach, in addition to further detailed discussions on the latest scientific instruments and individual detectors. The book is written in a very accessible manner, and most of the mathematics is accessible to those who have attended a mathematics course in their final years at school. Nevertheless, the treatment of the topics in general is at a sufficiently high level to be of use to those professionals seeking technical information in areas of astronomy with which they might not be completely familiar. Key Features: Details the instrumentation and theory of astronomical observations, including radio waves, gamma rays, cosmic rays, neutrinos, gravitational waves and dark matter and energy and more Presents the background theory and operating practice of state-of-the-art detectors and instruments Fully updated to contain the latest technology and research developments

Description Cooperative Gaming provides context and practical advice regarding diversity in the games industry. The book begins with a deep dive into research literature and the history of diversity in the games industry to provide context around what diversity is and why it is a topic worth considering. The book looks at the different facets of diversity and games, exploring the issues and solutions within game development, studio management, event planning, and more. It provides people with practical advice about being a marginalized person in the games industry and how to be heard, how studios can support inclusive practices, and events can actively become more accessible to a diverse audience. Key Features * Explores the history of diversity in games * Provides important information around what it is like to be a marginalized person in the industry * Gives practical steps to improve the inclusivity of the industry that are designed to aid in contextualizing and upskilling new developers Author Bios Alayna Cole is the managing director of Queerly Represent Me, a not-for-profit championing queer representation in games. Alayna is also a producer at Sledgehammer Games, co-chair of the IGDA LGBTQ+ special interest group, and an award-winning games journalist and game developer. She was featured on the 2016 and 2017 Develop Pacific 30 Under 30 lists and the 2017 and 2019 Develop Pacific Women in Games lists, and she has received several other accolades in the industry. Jessica Zammit started writing in 2013 for Start Select Media, and for the next five years she followed her interest in writing about representations of mental health, diversity, and particularly, sexuality in video games. Jessica has been speaking about diversity in games at conventions such as PAX Australia since 2016 and has been featured on several other discussions in and around the topic of representation in games and games criticism. Along with her co-author, she is co-chair of the IGDA LGBTQ+ special interest group, and she was featured on the 2018 Develop Pacific 30 Under 30 and Women in Games lists.

In today's world, deep learning source codes and a plethora of open access geospatial images are readily available and easily accessible. However, most people are missing the educational tools to make use of this resource. Deep Learning for Remote Sensing Images with Open Source Software is the first practical book to introduce deep learning techniques using free open source tools for processing real world remote sensing images. The approaches detailed in this book are generic and can be adapted to suit many different applications for remote sensing image processing, including landcover mapping, forestry, urban studies, disaster mapping, image restoration, etc. Written with practitioners and students in mind, this book helps link together the theory and practical use of existing tools and data to apply deep learning techniques on remote sensing images and data. Specific Features of this Book: The first book that explains how to apply deep learning techniques to public, free available data (Spot-7 and Sentinel-2 images, OpenStreetMap vector data), using open source software (QGIS, Orfeo ToolBox, TensorFlow) Presents approaches suited for real world images and data targeting large scale processing and GIS applications Introduces state of the art deep learning architecture families that can be applied to remote sensing world, mainly for landcover mapping, but also for generic approaches (e.g. image restoration) Suited for deep learning beginners and readers with some GIS knowledge. No coding knowledge is required to learn practical skills. Includes deep learning techniques through many step by step remote sensing data processing exercises.

Description Cooperative Gaming provides context and practical advice regarding diversity in the games industry. The book begins with a deep dive into research literature and the history of diversity in the games industry to provide context around what diversity is and why it is a topic worth considering. The book looks at the different facets of diversity and games, exploring the issues and solutions within game development, studio management, event planning, and more. It provides people with practical advice about being a marginalized person in the games industry and how to be heard, how studios can support inclusive practices, and events can actively become more accessible to a diverse audience. Key Features * Explores the history of diversity in games * Provides important information around what it is like to be a marginalized person in the industry * Gives practical steps to improve the inclusivity of the industry that are designed to aid in contextualizing and upskilling new developers Author Bios Alayna Cole is the managing director of Queerly Represent Me, a not-for-profit championing queer representation in games. Alayna is also a producer at Sledgehammer Games, co-chair of the IGDA LGBTQ+ special interest group, and an award-winning games journalist and game developer. She was featured on the 2016 and 2017 Develop Pacific 30 Under 30 lists and the 2017 and 2019 Develop Pacific Women in Games lists, and she has received several other accolades in the industry. Jessica Zammit started writing in 2013 for Start Select Media, and for the next five years she followed her interest in writing about representations of mental health, diversity, and particularly, sexuality in video games. Jessica has been speaking about diversity in games at conventions such as PAX Australia since 2016 and has been featured on several other discussions in and around the topic of representation in games and games criticism. Along with her co-author, she is co-chair of the IGDA LGBTQ+ special interest group, and she was featured on the 2018 Develop Pacific 30 Under 30 and Women in Games lists.

Inspired by Roland Barthes's practice of "semioclasm" in Mythologies, this book offers a "technoclasm"; a cultural critique of US narratives, discourses, images, and objects that have transformed the politics of automation into statements of fact about the "rise of the robots". Treating automation as an ensemble of technologies and science fictions, this book foregrounds automation's ideologies, exaggerations, failures, and mystifications of the social value of human labor in order to question accepted and prolific automation mythologies. Jesse Ramirez offers a study of automation that recognizes automation as a technosocial project, that uses the tools of cultural studies and history to investigate the narratives and ideologies that often implicitly frame the automation debate, and that concretely and soberly assesses the technologies that have made the headlines. The case studies featured include some of the most widely cited and celebrated automatic technologies, such as the Baxter industrial robot, the self-driving car, and the Watson AI system. An ideal resource for anyone interested in or studying emerging technology and society, automation, Marxist cultural theory, cultural studies, science fiction studies, and the cultural history of technology.

This book introduces the reader with little or no previous computer-programming experience to the Python programming language of interest for a physicist or a natural-sciences student. The book starts with basic interactive Python in order to acquire an introductory familiarity with the language, than tackle Python scripts (programs) of increasing complexity, that the reader is invited to run on her/his computer. All program listings are discussed in detail, and the reader is invited to experiment on what happens if some code lines are modified. The reader is introduced to Matplotlib graphics for the generation of figures representing data and function plots and, for instance, field lines. Animated function plots are also considered. A chapter is dedicated to the numerical solution of algebraic and transcendental equations, the basic mathematical principles are discussed and the available Python tools for the solution are presented. A further chapter is dedicated to the numerical solution of ordinary differential equations. This is of vital importance for the physicist, since differential equations are at the base of both classical physics (Newton's equations) and quantum mechanics (Schroedinger's equation). The shooting method for the numerical solution of ordinary differential equations with boundary conditions at two boundaries is also presented. Python programs for the solution of two quantum-mechanics problems are discussed as examples. Two chapters are dedicated to Tkinter graphics, which gives the user more freedom than Matplotlib, and to Tkinter animation. Programs displaying the animation of physical problems involving the solution of ordinary differential equations (for which in most cases there is no algebraic solution) in real time are presented and discussed. Finally, 3D animation is presented with Vpython.

This much-needed text brings the treatment of optical pattern recognition up-to-date in one comprehensive resource. Optical pattern recognition, one of the first implementations of Fourier Optics, is now widely used, and this text provides an accessible introduction for readers who wish to get to grips with how holography is applied in a practical context. A wide range of devices are addressed from a user perspective and are accompanied with detailed tables enabling performance comparison, in addition to chapters exploring computer-generated holograms, optical correlator systems, and pattern matching algorithms. This book will appeal to both lecturers and research scientists in the field of electro-optic devices and systems. Features: Covers a range of new developments, including computer-generated holography and 3D image recognition Accessible without a range of prior knowledge, providing a clear exposition of technically difficult concepts Contains extensive examples throughout to reinforce learning

Automatic biometrics recognition techniques are increasingly important in corporate and public security systems and have increased in methods due to rapid field development. This book discusses classic behavioral biometrics as well as collects the latest advances in techniques, theoretical approaches, and dynamic applications. This future-looking book is an important reference tool for researchers, practitioners, academicians, and technologists. While there are existing books that focus on physiological biometrics or algorithmic approaches deployed in biometrics, this book addresses a gap in the existing literature for a text that is solely dedicated to the topic of behavioral biometrics.

Handbook of Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing shows you how robust subspace learning and tracking by decomposition into low-rank and sparse matrices provide a suitable framework for computer vision applications. Incorporating both existing and new ideas, the book conveniently gives you one-stop access to a number of different decompositions, algorithms, implementations, and benchmarking techniques. Divided into five parts, the book begins with an overall introduction to robust principal component analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while the third part focuses on robust online subspace estimation, learning, and tracking. Covering applications in image and video processing, the fourth part discusses image analysis, image denoising, motion saliency detection, video coding, key frame extraction, and hyperspectral video processing. The final part presents resources and applications in background/foreground separation for video surveillance. With contributions from leading teams around the world, this handbook provides a complete overview of the concepts, theories, algorithms, and applications related to robust low-rank and sparse matrix decompositions. It is designed for researchers, developers, and graduate students in computer vision, image and video processing, real-time architecture, machine learning, and data mining.

Find the right algorithm for your image processing application Exploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and computer vision. The author covers all facets-geometric, statistical, and computational-of the methods. He looks at how the numerical algorithms relate to one another through underlying ideas, compares the strengths and weaknesses of each algorithm, and illustrates how to combine the algorithms to achieve the best performance. After introducing errors-in-variables (EIV) regression analysis and its history, the book summarizes the solution of the linear EIV problem and highlights its main geometric and statistical properties. It next describes the theory of fitting circles by least squares, before focusing on practical geometric and algebraic circle fitting methods. The text then covers the statistical analysis of curve and circle fitting methods. The last chapter presents a sample of "exotic" circle fits, including some mathematically sophisticated procedures that use complex numbers and conformal mappings of the complex plane. Essential for understanding the advantages and limitations of the practical schemes, this book thoroughly addresses the theoretical aspects of the fitting problem. It also identifies obscure issues that may be relevant in future research.

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing-one of the first books to integrate these topics together. By improving readers' knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples. A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry. Features Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images. Contains many examples, detailed derivations, and working Python examples of the techniques. Offers practical tips on image acquisition and processing. Includes numerous exercises to test the reader's skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book's web page. New to this edition Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks. A new chapter on affine transform and many new algorithms. Updated Python code aligned to the latest version of modules.

Over the past decade, the field of image processing has made tremendous advances. One type of image processing that is currently of particular interest is "tomographic imaging," a technique for computing the density function of a body, or discontinuity surfaces of this function. Today, tomography is widely used, and has applications in such fields as medicine, engineering, physics, geophysics, and security. The Radon Transform and Local Tomography clearly explains the theoretical, computational, and practical aspects of applied tomography. It includes sufficient background information to make it essentially self-contained for most readers.

Remote sensing of impervious surfaces has matured using advances in geospatial technology so recent that its applications have received only sporadic coverage in remote sensing literature. Remote Sensing of Impervious Surfaces is the first to focus entirely on this developing field. It provides detailed coverage of mapping, data extraction, and modeling techniques specific to analyzing impervious surfaces, such as roads and buildings. Written by renowned experts in the field, this book reviews the major approaches that apply to this emerging field as well as current challenges, developments, and trends. The authors introduce remote sensing digital image processing techniques for estimating and mapping impervious surfaces in urban and rural areas. Presenting the latest modeling tools and algorithms for data extraction and analysis, the book explains how to differentiate roads, roofs, and other manmade structures from remotely sensed images for individual analysis. The final chapters examine how to use impervious surface data for predicting the flow of storm- or floodwater and studying trends in population, land use, resource distribution, and other real-world applications in environmental, urban, and regional planning. Each chapter offers a consistent format including a concise review of basic concepts and methodologies, timely case studies, and guidance for solving problems and analyzing data using the techniques presented.

Medical image analysis using advanced fuzzy set theoretic techniques is an exciting and dynamic branch of image processing. Since the introduction of fuzzy set theory, there has been an explosion of interest in advanced fuzzy set theories-such as intuitionistic fuzzy and Type II fuzzy set-that represent uncertainty in a better way. Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques deals with the application of intuitionistic fuzzy and Type II fuzzy set theories for medical image analysis. Designed for graduate and doctorate students, this higher-level text: Provides a brief introduction to advanced fuzzy set theory, fuzzy/intuitionistic fuzzy aggregation operators, and distance/similarity measures Covers medical image enhancement using advanced fuzzy sets, including MATLAB (R)-based examples to increase contrast of the images Describes intuitionistic fuzzy and Type II fuzzy thresholding techniques that separate different regions/leukocyte types/abnormal lesions Demonstrates the clustering of unwanted lesions/regions even in the presence of noise by applying intuitionistic fuzzy clustering Highlights the edges of poorly illuminated images and uses intuitionistic fuzzy edge detection to find the edges of different regions Defines fuzzy mathematical morphology and explores its application using the Lukasiewicz operator, t-norms, and t-conorms Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques is useful not only for students, but also for teachers, engineers, scientists, and those interested in the field of medical image analysis. A basic knowledge of fuzzy set is required, along with a solid understanding of mathematics and image processing.

This volume gathers papers presented at the Workshop on Computational Diffusion MRI (CDMRI'18), which was held under the auspices of the International Conference on Medical Image Computing and Computer Assisted Intervention in Granada, Spain on September 20, 2018. It presents the latest developments in the highly active and rapidly growing field of diffusion MRI. The reader will find papers on a broad range of topics, from the mathematical foundations of the diffusion process and signal generation, to new computational methods and estimation techniques for the in-vivo recovery of microstructural and connectivity features, as well as harmonisation and frontline applications in research and clinical practice. The respective papers constitute invited works from high-profile researchers with a specific focus on three topics that are now gaining momentum within the diffusion MRI community: i) machine learning for diffusion MRI; ii) diffusion MRI outside the brain (e.g. in the placenta); and iii) diffusion MRI for multimodal imaging. The book shares new perspectives on the latest research challenges for those currently working in the field, but also offers a valuable starting point for anyone interested in learning computational techniques in diffusion MRI. It includes rigorous mathematical derivations, a wealth of full-colour visualisations, and clinically relevant results. As such, it will be of interest to researchers and practitioners in the fields of computer science, MRI physics and applied mathematics alike.

Hyperspectral Imaging: Techniques for Spectral Detection and Classification is an outgrowth of the research conducted over the years in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. It explores applications of statistical signal processing to hyperspectral imaging and further develops non-literal (spectral) techniques for subpixel detection and mixed pixel classification. This text is the first of its kind on the topic and can be considered a recipe book offering various techniques for hyperspectral data exploitation. In particular, some known techniques, such as OSP (Orthogonal Subspace Projection) and CEM (Constrained Energy Minimization) that were previously developed in the RSSIPL, are discussed in great detail. This book is self-contained and can serve as a valuable and useful reference for researchers in academia and practitioners in government and industry.

Information Visualization in the Era of Innovative Journalism brings together over 30 authors from countries around the world to synthesize how recent technological innovations have impacted the development, practice and consumption of contemporary journalism. As technology rapidly progresses, shifts, and innovates, there have been immense changes in the way we communicate. This book collects research from around the world that takes an in-depth look at the primary transformations related to journalistic innovation in recent times. High-profile contributors provide cutting-edge scholarship on innovation in journalism as it relates to emergent topics such as virtual reality, podcasting, multimedia infographics, social media, mobile storytelling and others. The book pays special attention to the development of information visualization and the ability of recent innovations to meet audience needs and desires. Students and scholars studying contemporary journalism history and practice will find this a vital and up-to-date resource, as well as those studying communication technology as it relates to marketing, PR or mass media broadly.