An Image Processing Tour of College Mathematics aims to provide meaningful context for reviewing key topics of the college mathematics curriculum, to help students gain confidence in using concepts and techniques of applied mathematics, to increase student awareness of recent developments in mathematical sciences, and to help students prepare for graduate studies. The topics covered include a library of elementary functions, basic concepts of descriptive statistics, probability distributions of functions of random variables, definitions and concepts behind first- and second-order derivatives, most concepts and techniques of traditional linear algebra courses, an introduction to Fourier analysis, and a variety of discrete wavelet transforms - all of that in the context of digital image processing. Features Pre-calculus material and basic concepts of descriptive statistics are reviewed in the context of image processing in the spatial domain. Key concepts of linear algebra are reviewed both in the context of fundamental operations with digital images and in the more advanced context of discrete wavelet transforms. Some of the key concepts of probability theory are reviewed in the context of image equalization and histogram matching. The convolution operation is introduced painlessly and naturally in the context of naive filtering for denoising and is subsequently used for edge detection and image restoration. An accessible elementary introduction to Fourier analysis is provided in the context of image restoration. Discrete wavelet transforms are introduced in the context of image compression, and the readers become more aware of some of the recent developments in applied mathematics. This text helps students of mathematics ease their way into mastering the basics of scientific computer programming.

This book presents the latest technological advances and practical tools for discovering, verifying and visualizing social media video content, and managing related rights. The digital media revolution is bringing breaking news to online video platforms, and news organizations often rely on user-generated recordings of new and developing events shared in social media to illustrate the story. However, in video, there is also deception. In today's "fake news" era, access to increasingly sophisticated editing and content management tools and the ease with which fake information spreads in electronic networks, require the entire news and media industries to carefully verify third-party content before publishing it. As such, this book is of interest to computer scientists and researchers, news and media professionals, as well as policymakers and data-savvy media consumers.

This book collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.

This book describes the signal, image and video processing methods and techniques for fire detection and provides a thorough and practical overview of this important subject, as a number of new methods are emerging. This book will serve as a reference for signal processing and computer vision, focusing on fire detection and methods for volume sensors. Applications covered in this book can easily be adapted to other domains, such as multi-modal object recognition in other safety and security problems, with scientific importance for fire detection, as well as video surveillance. Coverage includes: Camera Based Techniques Multi-modal/Multi-sensor fire analysis Pyro-electric Infrared Sensors for Flame Detection Large scale fire experiments Wildfire detection from moving aerial platforms

Digital forensics deals with the acquisition, preservation, examination, analysis and presentation of electronic evidence. Computer networks, cloud computing, smartphones, embedded devices and the Internet of Things have expanded the role of digital forensics beyond traditional computer crime investigations. Practically every crime now involves some aspect of digital evidence; digital forensics provides the techniques and tools to articulate this evidence in legal proceedings. Digital forensics also has myriad intelligence applications; furthermore, it has a vital role in cyber security -- investigations of security breaches yield valuable information that can be used to design more secure and resilient systems. Advances in Digital Forensics XV describes original research results and innovative applications in the discipline of digital forensics. In addition, it highlights some of the major technical and legal issues related to digital evidence and electronic crime investigations. The areas of coverage include: forensic models, mobile and embedded device forensics, filesystem forensics, image forensics, and forensic techniques. This book is the fifteenth volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.9 on Digital Forensics, an international community of scientists, engineers and practitioners dedicated to advancing the state of the art of research and practice in digital forensics. The book contains a selection of fourteen edited papers from the Fifteenth Annual IFIP WG 11.9 International Conference on Digital Forensics, held in Orlando, Florida, USA in the winter of 2019. Advances in Digital Forensics XV is an important resource for researchers, faculty members and graduate students, as well as for practitioners and individuals engaged in research and development efforts for the law enforcement and intelligence communities.

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.

a balanced blend of theoretical and practical information that enables readers to develop 3D worlds quickly and efficiently.

With annual gross sales surpassing 100 billion U.S. dollars each of the last two years, the digital games industry may one day challenge theatrical-release movies as the highest-grossing entertainment media in the world. In their examination of the tremendous cultural influence of digital games, Daniel Reardon and David Wright analyze three companies that have shaped the industry: Bethesda, located in Rockville, Maryland, USA; BioWare in Edmonton, Alberta, Canada; and CD Projekt Red in Warsaw, Poland. Each company has used social media and technical content in the games to promote players' belief that players control the companies' game narratives. The result has been at times explosive, as empowered players often attempted to co-op the creative processes of games through discussion board forum demands, fund-raising campaigns to persuade companies to change or add game content, and modifications ("modding") of the games through fan-created downloads. The result has changed the way we understand the interactive nature of digital games and the power of fan culture to shape those games.

Quad Rotorcraft Control develops original control methods for the navigation and hovering flight of an autonomous mini-quad-rotor robotic helicopter. These methods use an imaging system and a combination of inertial and altitude sensors to localize and guide the movement of the unmanned aerial vehicle relative to its immediate environment.
The history, classification and applications of UAVs are introduced, followed by a description of modelling techniques for quad-rotors and the experimental platform itself. A control strategy for the improvement of attitude stabilization in quad-rotors is then proposed and tested in real-time experiments. The strategy, based on the use low-cost components and with experimentally-established robustness, avoids drift in the UAV s angular position by the addition of an internal control loop to each electronic speed controller ensuring that, during hovering flight, all four motors turn at almost the same speed. The quad-rotor s Euler angles being very close to the origin, other sensors like GPS or image-sensing equipment can be incorporated to perform autonomous positioning or trajectory-tracking tasks.
Two vision-based strategies, each designed to deal with a specific kind of mission, are introduced and separately tested. The first stabilizes the quad-rotor over a landing pad on the ground; it extracts the 3-dimensional position using homography estimation and derives translational velocity by optical flow calculation. The second combines colour-extraction and line-detection algorithms to control the quad-rotor s 3-dimensional position and achieves forward velocity regulation during a road-following task.
In order to estimate the translational-dynamical characteristics of the quad-rotor (relative position and translational velocity) as they evolve within a building or other unstructured, GPS-deprived environment, imaging, inertial and altitude sensors are combined in a state observer. The text give the reader a current view of the problems encountered in UAV control, specifically those relating to quad-rotor flying machines and it will interest researchers and graduate students working in that field. The vision-based control strategies presented help the reader to a better understanding of how an imaging system can be used to obtain the information required for performance of the hovering and navigation tasks ubiquitous in rotored UAV operation."

The book provides future research directions in IoT and image processing based Energy, Industry, and Healthcare domain and explores the different applications of its associated technologies. However, the Internet of Things and image processing is a very big field with a lot of subfields, which are very important such as Smart Homes to improve our daily life, Smart Cities to improve the citizens' life, Smart Towns to recover the livability and traditions, Smart Earth to protect our world, and Industrial Internet of Things to create safer and easier jobs. This book considers very important research areas in Energy, Industry, and Healthcare domain with IoT and image processing applications.The aim of the book to highlights future directions of optimization methods in various engineering and science applications in various IoT and image processing applications. Emphasis is given to deep learning and similar models of neural network-based learning techniques employed in solving optimization problems of different engineering and science applications. The role of AI in mechatronics is also highlighted using suitable optimization methods. This book considers very important research areas in Energy, Industry, and Healthcare. It addresses major issues and challenges in Energy, Industry, and Healthcare and solutions proposed for IoT-enabled cellular/computer networks, routing/communication protocols, surveillances applications, secured data management, and positioning approaches. It focuses mainly on smart and context-aware implementations. Key sailing Features: The impact of the proposed book is to provide a major area of concern to develop a foundation for the implementation process of new image processing and IoT devices based on Energy, Industry, and Healthcare related technology. The researchers working on image processing and IoT devices can correlate their work with other requirements of advanced technology in Energy, Industry, and Healthcare domain. To make aware of the latest technology like AI and Machine learning in Energy, Industry, and Healthcare related technology. Useful for the researcher to explore new things like Security, cryptography, and privacy in Energy, Industry, and Healthcare related technology. People who want to start in Energy, Industry, and Healthcare related technology with image processing and IoT world.

This book explores the use of a socio-inspired optimization algorithm (the Cohort Intelligence algorithm), along with Cognitive Computing and a Multi-Random Start Local Search optimization algorithm. One of the most important types of media used for steganography is the JPEG image. Considering four important aspects of steganography techniques - picture quality, high data-hiding capacity, secret text security and computational time - the book provides extensive information on four novel image-based steganography approaches that employ JPEG compression. Academics, scientists and engineers engaged in research, development and application of steganography techniques, optimization and data analytics will find the book's comprehensive coverage an invaluable resource.

Change Detection and Image Time Series Analysis 1 presents a wide range of unsupervised methods for temporal evolution analysis through the use of image time series associated with optical and/or synthetic aperture radar acquisition modalities. Chapter 1 introduces two unsupervised approaches to multiple-change detection in bi-temporal multivariate images, with Chapters 2 and 3 addressing change detection in image time series in the context of the statistical analysis of covariance matrices. Chapter 4 focuses on wavelets and convolutional-neural filters for feature extraction and entropy-based anomaly detection, and Chapter 5 deals with a number of metrics such as cross correlation ratios and the Hausdorff distance for variational analysis of the state of snow. Chapter 6 presents a fractional dynamic stochastic field model for spatio temporal forecasting and for monitoring fast-moving meteorological events such as cyclones. Chapter 7 proposes an analysis based on characteristic points for texture modeling, in the context of graph theory, and Chapter 8 focuses on detecting new land cover types by classification-based change detection or feature/pixel based change detection. Chapter 9 focuses on the modeling of classes in the difference image and derives a multiclass model for this difference image in the context of change vector analysis.

Change Detection and Image Time Series Analysis 2 presents supervised machine-learning-based methods for temporal evolution analysis by using image time series associated with Earth observation data. Chapter 1 addresses the fusion of multisensor, multiresolution and multitemporal data. It proposes two supervised solutions that are based on a Markov random field: the first relies on a quad-tree and the second is specifically designed to deal with multimission, multifrequency and multiresolution time series. Chapter 2 provides an overview of pixel based methods for time series classification, from the earliest shallow learning methods to the most recent deep-learning-based approaches. Chapter 3 focuses on very high spatial resolution data time series and on the use of semantic information for modeling spatio-temporal evolution patterns. Chapter 4 centers on the challenges of dense time series analysis, including pre processing aspects and a taxonomy of existing methodologies. Finally, since the evaluation of a learning system can be subject to multiple considerations, Chapters 5 and 6 offer extensive evaluations of the methodologies and learning frameworks used to produce change maps, in the context of multiclass and/or multilabel change classification issues.

Successful remote sensing methods and applications are rooted in the science, art, and technology of earth observation, part of the larger emerging world of geographical information science. Sensors are increasingly sensitive to the phenomena we wish to observe and image analysis systems are increasingly able to transform the data and deliver the required information. At the same time, advances in forest science and management continue to develop momentum. A renewed commitment to understanding forests at different scales and with a process-based perspective has helped generate demand for information about forests that is feasibly acquired only by remote sensing.

Remote Sensing of Forest Environments: Concepts and Case Studies is an edited volume intended to provide readers with a state-of-the-art synopsis of the current methods and applied applications employed in remote sensing the world's forests. The contributing authors have sought to illustrate and deepen our understanding of remote sensing of forests, providing new insights and indicating opportunities that are created when forests and forest practices are considered in concert with the evolving paradigm of remote sensing science. Following background and methods sections, this book introduces a series of case studies that exemplify the ways in which remotely sensed data are operationally used, as an element of the decision-making process, and in the scientific study of forests.

Remote Sensing of Forest Environments: Concepts and Case Studies is designed to meet the needs of a professional audience composed of both practitioners and researchers. This book is also suitable as a secondary text for graduate-level students in Forestry, Environmental Science, Geography, Engineering, and Computer Science.

Image processing and machine vision are fields of renewed interest in the commercial market. People in industry, managers, and technical engineers are looking for new technologies to move into the market. Many of the most promising developments are taking place in the field of image processing and its applications. The book offers a broad coverage of advances in a range of topics in image processing and machine vision.

This volume helps to fill the gap between data analytics, image processing, and soft computing practices. Soft computing methods are used to focus on data analytics and image processing to develop good intelligent systems. To this end, readers of this volume will find quality research that presents the current trends, advanced methods, and hybridized techniques relating to data analytics and intelligent systems. The book also features case studies related to medical diagnosis with the use of image processing and soft computing algorithms in particular models. Providing extensive coverage of biometric systems, soft computing, image processing, artificial intelligence, and data analytics, the chapter authors discuss the latest research issues, present solutions to research problems, and look at comparative analysis with earlier results. Topics include some of the most important challenges and discoveries in intelligent systems today, such as computer vision concepts and image identification, data analysis and computational paradigms, deep learning techniques, face and speaker recognition systems, and more.

The second edition of Disney Stories: Getting to Digital will be of interest to lovers of Disney history and also to lovers of Hollywood history in general. The first edition was planned as a short history of the companies evolution from analog storytelling to a digital online presence that closed the chapter on early Disney films with the release of the groundbreaking Snow White. The purpose of the new edition is to bring to readers a more complete view of the analog-digital story by including three new chapters on film that cover key developments from the live-animation hybrids of the 1940s to CAPS and CGI in the 1990s and VR in the 2010s. It also includes in the discussion of cross-media storytelling the acquisition of the exceptional story property, Star Wars, and discusses how Disney has brought the epic into the Disney Master Narrative by creating Galaxy's Edge in its US theme parks. Krystina Madej's engaging portrayal of the long history of Disney's love affair with storytelling and technology brings to life the larger focus of innovation in creating characters and stories that captivate an audience, and together with Newton Lee's detailed experience of Disney during the crucial 1995-2005 era when digital innovation in online and games was at its height in the company, makes for a fast-paced captivating read. Disney Stories first edition explored the history of Disney, both analog and digital. It described in detail how Walt Disney used inventive and often ground-breaking approaches in the use of sound, color, depth, and the psychology of characters to move the animation genre from short visual gags to feature-length films with meaningful stories that engaged audience's hearts as well as tickled their funny bones. It showed Walt's comprehensive approach to engaging the public across all media as he built the Disney Master Narrative by using products, books, comics, public engagements, fan groups such as the Mickey Mouse club, TV, and, of course, Disneyland, his theme park. Finally it showed how, after his passing, the company continued to embrace Walt's enthusiasm for using new technology to engage audiences through their commitment to innovation in digital worlds. It describes in detail the innovative storybook CD-ROMs, their extensive online presence, the software they used and created for MMORGs such as Toontown, and the use of production methods such as agile methodology. This new edition provides insight on major developments in Disney films that moved them into the digital world.

Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. Includes over 200 equations that illustrate how to follow examples in the book.

Provides a comprehensive guide about how to use machine vision for Industry 4.0 applications like analysis of images for automated inspections, object detection, object tracking etc. Includes case studies of Robotics Internet of Things with its current and future applications in Healthcare, Agriculture, Transportation, etc. It highlights the inclusion of impaired people in industry, like intelligent assistant that helps deaf-mute people to transmit instructions and warnings in a manufacturing process. It examines the significant technological advancements in machine vision for industrial Internet of things and explores the commercial benefits using the real world applications from healthcare to transportation. Provides a conceptual framework of Machine vision for the various Industrial applications. Addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and post-graduate students, researchers, and anyone else interested in the trends, development, and opportunities for the Machine Vision for Industry 4.0 applications.

3D rotation analysis is widely encountered in everyday problems thanks to the development of computers. Sensing 3D using cameras and sensors, analyzing and modeling 3D for computer vision and computer graphics, and controlling and simulating robot motion all require 3D rotation computation. This book focuses on the computational analysis of 3D rotation, rather than classical motion analysis. It regards noise as random variables and models their probability distributions. It also pursues statistically optimal computation for maximizing the expected accuracy, as is typical of nonlinear optimization. All concepts are illustrated using computer vision applications as examples. Mathematically, the set of all 3D rotations forms a group denoted by SO(3). Exploiting this group property, we obtain an optimal solution analytical or numerically, depending on the problem. Our numerical scheme, which we call the "Lie algebra method," is based on the Lie group structure of SO(3). This book also proposes computing projects for readers who want to code the theories presented in this book, describing necessary 3D simulation setting as well as providing real GPS 3D measurement data. To help readers not very familiar with abstract mathematics, a brief overview of quaternion algebra, matrix analysis, Lie groups, and Lie algebras is provided as Appendix at the end of the volume.

An up-to-date analysis of the SAR wavefront reconstruction signal theory and its digital implementation With the advent of fast computing and digital information processing techniques, synthetic aperture radar (SAR) technology has become both more powerful and more accurate. Synthetic Aperture Radar Signal Processing with MATLAB Algorithms addresses these recent developments, providing a complete, up-to-date analysis of SAR and its associated digital signal processing algorithms. This book introduces the wavefront reconstruction signal theory that underlies the best SAR imaging methods and provides clear guidelines to system design, implementation, and applications in diverse areas—from airborne reconnaissance to topographic imaging of ocean floors to surveillance and air traffic control to medical imaging techniques, and numerous others. Enabling professionals in radar signal and image processing to use synthetic aperture technology to its fullest potential, this work:

• Includes M-files to supplement this book that can be retrieved from The MathWorks anonymous FTP server at ftp://ftp.mathworks.com/pub/books/soumekh
• Provides practical examples and results from real SAR, ISAR, and CSAR databases
• Outlines unique properties of the SAR signal that cannot be found in other information processing systems
• Examines spotlight SAR, stripmap SAR, circular SAR, and monopulse SAR modalities
• Discusses classical SAR processing issues such as motion compensation and radar calibration

A Selection of Image Processing Techniques: From Fundamentals to Research Front focuses on seven commonly used image-processing techniques. These are de-noising, de-blurring, repairing, de-fogging, reconstruction from projection, watermarking, and super-resolution. This book is suitable for readers who do not have a complete foundation in the principles of image technology but need to use image techniques to solve specific tasks in particular applications. Hence, elementary knowledge for further study is provided, allowing the reader to discover suitable techniques for solving practical problems and to learn the latest developments in a specific domain. This book offers readers a three-step strategy toward problem solving: first, essential principles, then, a detailed explanation, and finally, a discussion of practical and working techniques for specific tasks. Throughout, the author highlights materials pertaining to the newest developments and trends of the technologies.

Although the field of texture processing is now well-established, research in this area remains predominantly restricted to texture analysis and simple and approximate static textures.

This comprehensive text/reference presents a survey of the state of the art in multidimensional, physically-correct visual texture modeling. Starting from basic principles and building upon the fundamentals to the latest advanced methods, the book brings together research from computer vision, pattern recognition, computer graphics, virtual and augmented reality. The text assumes a graduate-level understanding of statistics and probability theory, and a knowledge of basic computer graphics principles, but is accessible to newcomers to the field.

Topics and features: reviews the entire process of texture synthesis, including material appearance representation, measurement, analysis, compression, modeling, editing, visualization, and perceptual evaluation; explains the derivation of the most common representations of visual texture, discussing their properties, advantages, and limitations; describes a range of techniques for the measurement of visual texture, including BRDF, SVBRDF, BTF and BSSRDF; investigates the visualization of textural information, from texture mapping and mip-mapping to illumination- and view-dependent data interpolation; examines techniques for perceptual validation and analysis, covering both standard pixel-wise similarity measures and also methods of visual psychophysics; reviews the applications of visual textures, from visual scene analysis in image processing and medical applications, to high-quality visualizations for cultural heritage and the automotive industry.

Researchers, lecturers, students and practitioners will all find this book an invaluable reference on the rapidly developing new field of texture modeling.

The latest edition provides a comprehensive foundation for image and video compression. It covers HEVC/H.265 and future video coding activities, in addition to Internet Video Coding. The book features updated chapters and content, along with several new chapters and sections. It adheres to the current international standards, including the JPEG standard.

This book explores the methods needed for creating and manipulating HDR content. HDR is a step change from traditional imaging; more closely matching what we see with our eyes. In the years since the first edition of this book appeared, HDR has become much more widespread, moving from a research concept to a standard imaging method. This new edition incorporates all the many developments in HDR since the first edition and once again emphasizes practical tips, including the authors' popular HDR Toolbox (available on the authors' website) for MATLAB and gives readers the tools they need to develop and experiment with new techniques for creating compelling HDR content. Key Features: Contains the HDR Toolbox for readers' experimentation on authors' website Offers an up-to-date, detailed guide to the theory and practice of high dynamic range imaging Covers all aspects of the field, from capture to display Provides benchmarks for evaluating HDR imagery