This book presents works detailing the application of processing and visualization techniques for analyzing the Earth's subsurface. The topic of the book is interactive data processing and interactive 3D visualization techniques used on subsurface data. Interactive processing of data together with interactive visualization is a powerful combination which has in the recent years become possible due to hardware and algorithm advances in. The combination enables the user to perform interactive exploration and filtering of datasets while simultaneously visualizing the results so that insights can be made immediately. This makes it possible to quickly form hypotheses and draw conclusions. Case studies from the geosciences are not as often presented in the scientific visualization and computer graphics community as e.g., studies on medical, biological or chemical data. This book will give researchers in the field of visualization and computer graphics valuable insight into the open visualization challenges in the geosciences, and how certain problems are currently solved using domain specific processing and visualization techniques. Conversely, readers from the geosciences will gain valuable insight into relevant visualization and interactive processing techniques. Subsurface data has interesting characteristics such as its solid nature, large range of scales and high degree of uncertainty, which makes it challenging to visualize with standard methods. It is also noteworthy that parallel fields of research have taken place in geosciences and in computer graphics, with different terminology when it comes to representing geometry, describing terrains, interpolating data and (example-based) synthesis of data. The domains covered in this book are geology, digital terrains, seismic data, reservoir visualization and CO2 storage. The technologies covered are 3D visualization, visualization of large datasets, 3D modelling, machine learning, virtual reality, seismic interpretation and multidisciplinary collaboration. People within any of these domains and technologies are potential readers of the book.

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.

Active RC filters were first applied in the late 1950s. Since then, there has been a rapid development in both theoretical research and practical realization methods, as witnessed by the appearance of some 3,000 publications on active RC filters. This abundance of literature has, however, caused a great deal of confusion for non-specialist engineers. In order to solve a problem of filter design, a prolonged study is usually needed in order to make the correct choice between a wide variety of filter structures. Furthermore, most publications are intended to solve detailed problems for experts in the field, with little useful contribution for practising electrical engineers.
Now, with the aid of this book, the designer can find the structure and circuit elements of a specified active RC filter with relatively few calculations. Moreover, the filter thus designed will have transfer characteristics within the specified tolerances, and will comprise the least expensive (i.e. highest tolerance) components.

The book discusses the impact of machine learning and computational intelligent algorithms on medical image data processing, and introduces the latest trends in machine learning technologies and computational intelligence for intelligent medical image analysis. The topics covered include automated region of interest detection of magnetic resonance images based on center of gravity; brain tumor detection through low-level features detection; automatic MRI image segmentation for brain tumor detection using the multi-level sigmoid activation function; and computer-aided detection of mammographic lesions using convolutional neural networks.

The topic of level sets is currently very timely and useful for creating realistic 3-D images and animations. They are powerful numerical techniques for analyzing and computing interface motion in a host of application settings. In computer vision, it has been applied to stereo and segmentation, whereas in graphics it has been applied to the postproduction process of in-painting and 3-D model construction. Osher is co-inventor of the Level Set Methods, a pioneering framework introduced jointly with James Sethian from the University of Berkeley in 1998. This methodology has been used up to now to provide solutions to a wide application range not limited to image processing, computer vision, robotics, fluid mechanics, crystallography, lithography, and computer graphics. The topic is of great interest to advanced students, professors, and R&D professionals working in the areas of graphics (post-production), video-based surveillance, visual inspection, augmented reality, document image processing, and medical image processing. These techniques are already employed to provide solutions and products in the industry (Cognitech, Siemens, Philips, Focus Imaging). An essential compilation of survey chapters from the leading researchers in the field, emphasizing the applications of the methods. This book can be suitable for a short professional course related with the processing of visual information.

The explosion of computer use and internet communication has placed new emphasis on the ability to store, retrieve and search for all types of images, both still photo and video images. The success and the future of visual information retrieval depends on the cutting edge research and applications explored in this book. It combines the expertise from both computer vision and database research.
Unlike text retrieval and text/numeric databases the challenges of image databases are enormous. How do you use "data mining" to search for an image if you do not have "key words" to search? Exploratory Image Databases introduces the idea that it is possible to solve this problem by merging database systems into a single search and browse activity called "exploration."
Exploratory Image Databases is one of the first single-author books that unifies the critical emerging topic of image databases. A new approach to image databases, the work is divided into four central parts: introduction to the problems that image database research must solve; computer vision and information retrieval techniques; image database issues; and interface and engines for visual searches.
Example: Imagine the difficulty of building and using a database for "face recognition," where an image of a face is used. In order to effectively use the image a huge number of characteristics would need to be entered in the database. The goal of future image databases is to use hardware and software to recognize and categorize images without typing in characteristics.
* Comprehensive coverage of the image analysis as well as the database/theoretical aspects of image databases.
* Extensive coverage of interfaces and interaction models, with a theoretical framework for the development of new interaction schemes.
* Identifies three interaction models between users and image databases, two of which have no counterpart in traditional databases.
* Coverage of the relation between image and text, including mixed search models and the automatic determination of the relation between images and text on large corpuses like the web.
* Analysis of the process of signification in images and its influence on the interaction models and technological problems of image databases.

Meta-Learning, or learning to learn, has become increasingly popular in recent years. Instead of building AI systems from scratch for each machine learning task, Meta-Learning constructs computational mechanisms to systematically and efficiently adapt to new tasks. The meta-learning paradigm has great potential to address deep neural networks' fundamental challenges such as intensive data requirement, computationally expensive training, and limited capacity for transfer among tasks. This book provides a concise summary of Meta-Learning theories and their diverse applications in medical imaging and health informatics. It covers the unifying theory of meta-learning and its popular variants such as model-agnostic learning, memory augmentation, prototypical networks, and learning to optimize. The book brings together thought leaders from both machine learning and health informatics fields to discuss the current state of Meta-Learning, its relevance to medical imaging and health informatics, and future directions.

In the past several years, there have been significant technological advances in the field of crisis response. However, many aspects concerning the efficient collection and integration of geo-information, applied semantics and situation awareness for disaster management remain open. Improving crisis response systems and making them intelligent requires extensive collaboration between emergency responders, disaster managers, system designers and researchers alike. To facilitate this process, the Gi4DM (GeoInformation for Disaster Management) conferences have been held regularly since 2005. The events are coordinated by the Joint Board of Geospatial Information Societies (JB GIS) and ICSU GeoUnions. This book presents the outcomes of the Gi4DM 2018 conference, which was organised by the ISPRS-URSI Joint Working Group ICWG III/IVa: Disaster Assessment, Monitoring and Management and held in Istanbul, Turkey on 18-21 March 2018. It includes 12 scientific papers focusing on the intelligent use of geo-information, semantics and situation awareness.

This book contains the research on modeling bodies, cloth and character based adaptation performed during the last 3 years at MIRALab at the University of Geneva. More than ten researchers have worked together in order to reach a truly 3D Virtual Try On. What we mean by Virtual Try On is the possibility of anyone to give dimensions on her predefined body and obtain her own sized shape body, select a 3D cloth and see oneself animated in Real-Time, walking along a catwalk. Some systems exist today but are unable to adapt to body dimensions, have no real-time animation of body and clothes. A truly system on the web of Virtual Try On does not exist so far. This book is an attempt to explain how to build a 3D Virtual Try On system which is now very much in demand in the clothing industry. To describe this work, the book is divided into five chapters. The first chapter contains a brief historical background of general deformation methods. It ends with a section on the 3D human body scanner systems that are used both for rapid p- totyping and statistical analyses of the human body size variations.

This book focuses on deep learning-based methods for hyperspectral image (HSI) analysis. Unsupervised spectral-spatial adaptive band-noise factor-based formulation is devised for HSI noise detection and band categorization. The method to characterize the bands along with the noise estimation of HSIs will benefit subsequent remote sensing techniques significantly. This book develops on two fronts: On the one hand, it is aimed at domain professionals who want to have an updated overview of how hyperspectral acquisition techniques can combine with deep learning architectures to solve specific tasks in different application fields. On the other hand, the authors want to target the machine learning and computer vision experts by giving them a picture of how deep learning technologies are applied to hyperspectral data from a multidisciplinary perspective. The presence of these two viewpoints and the inclusion of application fields of remote sensing by deep learning are the original contributions of this review, which also highlights some potentialities and critical issues related to the observed development trends.

Signal Recovery Techniques for Image and Video Compression and Transmission establishes a bridge between the fields of signal recovery and image and video compression. Traditionally these fields have developed separately because the problems they examined were regarded as very different, and the techniques used appear unrelated. Recently, though, there is growing consent among the research community that the two fields are quite closely related. Indeed, in both fields the objective is to reconstruct the best possible signal from limited information. The field of signal recovery, which is relatively mature, has long been associated with a wealth of powerful mathematical techniques such as Bayesian estimation and the theory of projects onto convex sets (to name just two). This book illustrates for the first time in a complete volume how these techniques can be brought to bear on the very important problems of image and video compression and transmission. Signal Recovery Techniques for Image and Video Compression and Transmission, which is written by leading practitioners in both fields, is one of the first references that addresses this approach and serves as an excellent information source for both researchers and practicing engineers.

Considerable evidence exists that visual sensory information is analyzed simultaneously along two or more independent pathways. In the past two decades, researchers have extensively used the concept of parallel visual channels as a framework to direct their explorations of human vision. More recently, basic and clinical scientists have found such a dichotomy applicable to the way we organize our knowledge of visual development, higher order perception, and visual disorders, to name just a few. This volume attempts to provide a forum for gathering these different perspectives.

This book provides basic theories and implementations using SCILAB open-source software for digital images. The book simplifies image processing theories and well as implementation of image processing algorithms, making it accessible to those with basic knowledge of image processing. This book includes many SCILAB programs at the end of each theory, which help in understanding concepts. The book includes more than sixty SCILAB programs of the image processing theory. In the appendix, readers will find a deeper glimpse into the research areas in the image processing.

Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences. After discussing the characterizing properties of abstraction, a formal model, the KRA model, is presented to capture them. This model makes the notion of abstraction easily applicable by means of the introduction of a set of abstraction operators and abstraction patterns, reusable across different domains and applications. It is the impact of abstraction in Artificial Intelligence, Complex Systems and Machine Learning which creates the core of the book. A general framework, based on the KRA model, is presented, and its pragmatic power is illustrated with three case studies: Model-based diagnosis, Cartographic Generalization, and learning Hierarchical Hidden Markov Models.

The related fields of fractal image encoding and fractal image analysis have blossomed in recent years. This book, originating from a NATO Advanced Study Institute held in 1995, presents work by leading researchers. It is developing the subjects at an introductory level, but it also has some recent and exciting results in both fields.
The book contains a thorough discussion of fractal image compression and decompression, including both continuous and discrete formulations, vector space and hierarchical methods, and algorithmic optimizations. The book also discusses multifractal approaches to image analysis, segmentation, and recognition, including medical applications.

"La narraci6n literaria es la evocaci6n de las nostalgias. " ("Literary narration is the evocation of nostalgia. ") G. G. Marquez, interview in Puerta del Sol, VII, 4, 1996. A Personal Prehistory In 1972 I started cooperating with members of the Biodynamics Research Unit at the Mayo Clinic in Rochester, Minnesota, which was under the direction of Earl H. Wood. At that time, their ambitious (and eventually realized) dream was to build the Dynamic Spatial Reconstructor (DSR), a device capable of collecting data regarding the attenuation of X-rays through the human body fast enough for stop-action imaging the full extent of the beating heart inside the thorax. Such a device can be applied to study the dynamic processes of cardiopulmonary physiology, in a manner similar to the application of an ordinary cr (computerized tomography) scanner to observing stationary anatomy. The standard method of displaying the information produced by a cr scanner consists of showing two-dimensional images, corresponding to maps of the X-ray attenuation coefficient in slices through the body. (Since different tissue types attenuate X-rays differently, such maps provide a good visualization of what is in the body in those slices; bone - which attenuates X-rays a lot - appears white, air appears black, tumors typically appear less dark than the surrounding healthy tissue, etc. ) However, it seemed to me that this display mode would not be appropriate for the DSR.

Microscope Image Processing, Second Edition, introduces the basic fundamentals of image formation in microscopy including the importance of image digitization and display, which are key to quality visualization. Image processing and analysis are discussed in detail to provide readers with the tools necessary to improve the visual quality of images, and to extract quantitative information. Basic techniques such as image enhancement, filtering, segmentation, object measurement, and pattern recognition cover concepts integral to image processing. In addition, chapters on specific modern microscopy techniques such as fluorescence imaging, multispectral imaging, three-dimensional imaging and time-lapse imaging, introduce these key areas with emphasis on the differences among the various techniques. The new edition discusses recent developments in microscopy such as light sheet microscopy, digital microscopy, whole slide imaging, and the use of deep learning techniques for image segmentation and analysis with big data image informatics and management. Microscope Image Processing, Second Edition, is suitable for engineers, scientists, clinicians, post-graduate fellows and graduate students working in bioengineering, biomedical engineering, biology, medicine, chemistry, pharmacology and related fields, who use microscopes in their work and would like to understand the methodologies and capabilities of the latest digital image processing techniques or desire to develop their own image processing algorithms and software for specific applications.

Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data. This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.

Ultra-High Field Neuro MRI is a comprehensive reference and educational resource on the current state of neuroimaging at ultra-high field (UHF), with an emphasis on 7T. Sections cover the MR physics aspects of UHF, including the technical challenges and practical solutions that have enabled the rapid growth of 7T MRI. Individual chapters are dedicated to the different techniques that most strongly benefit from UHF, as well as chapters with a focus on different application areas in anatomical, functional and metabolic imaging. Finally, several chapters highlight the neurological and psychiatric applications for which 7T has shown benefits. The book is aimed at scientists who develop MR technologies and support clinical and neuroscience research, as well as users who want to benefit from UHF neuro MR techniques in their work. It also provides a comprehensive introduction to the field.

DSP Integrated Circuits establishes the essential interface between theory of digital signal processing algorithms and their implementation in full-custom CMOS technology. With an emphasis on techniques for co-design of DSP algorithms and hardware in order to achieve high performance in terms of throughput, low power consumption, and design effort, this book provides the professional engineer, researcher, and student with a firm foundation in the theoretical as well as the practical aspects of designing high performance DSP integrated circuits.
Centered around three design case studies, DSP Integrated Circuits thoroughly details a high-performance FFT processor, a 2-D Discrete Cosine Transform for HDTV, and a wave digital filter for interpolation of the sampling frequency. The case studies cover the essential parts of the design process in a top-down manner, from specification of algorithm design and optimization, scheduling of operations, synthesis of optimal architectures, realization of processing elements, to the floor-planning of the integrated circuit.
* Details the theory and design of digital filters - particularly wave digital filters, multi-rate digital filters, fast Fourier transforms (FFT's), and discrete cosine transforms (DCT's)
* Follows three complete "real-world" case studies throughout the book
* Provides complete coverage of finite word length effects in DSP algorithms
* In-depth survey of the computational properties of DSP algorithms and their mapping to optimal architectures
* Outlines DSP architectures and parallel, bit-serial, and distributed arithmetic
* Presents the design process in a top-down manner and incorporates numerous problemsand solutions

In contrast with trichromatic image sensors, imaging spectroscopy can capture the properties of the materials in a scene. This implies that scene analysis using imaging spectroscopy has the capacity to robustly encode material signatures, infer object composition and recover photometric parameters.

This landmark text/reference presents a detailed analysis of spectral imaging, describing how it can be used in elegant and efficient ways for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications from surveillance and computational photography, to biosecurity and resource exploration.

Topics and features: discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation; examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery; describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra; reviews the use of imaging spectroscopy for material identification; explores the recovery of reflection geometry from image reflectance; investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view.

An essential resource for researchers and graduate students of computer vision and pattern recognition, this comprehensive introduction to imaging spectroscopy for scene analysis will also be of great use to practitioners interested in shape analysis employing polarimetric imaging, and material recognition and classification using hyperspectral or multispectral data.

This book lays out all the latest research in the area of multimedia data hiding. The book introduces multimedia signal processing and information hiding techniques. It includes multimedia representation, digital watermarking fundamentals and requirements of watermarking. It moves on to cover the recent advances in multimedia signal processing, before presenting information hiding techniques including steganography, secret sharing and watermarking. The final part of this book includes practical applications of intelligent multimedia signal processing and data hiding systems.

Advanced Video-Based Surveillance Systems presents second generation surveillance systems that automatically process large sets of signals for performance monitoring tasks. Included is coverage of different architecture designs, customization of surveillance architecture for end-users, advances in the processing of imaging sequences, security systems, sensors, and remote monitoring projects. Examples are provided of surveillance applications in highway traffic control, subway stations, wireless communications, and other areas. This work will be of interest to researchers in image processing, computer vision, digital signal processing, and telecommunications.

Information technology is the enabling foundation for all of human activity at the beginning of the 21st century, and advances in this area are crucial to all of us. These advances are taking place all over the world and can only be followed and perceived when researchers from all over the world assemble, and exchange their ideas in conferences such as the one presented in this proceedings volume regarding the 26th International Symposium on Computer and Information Systems, held at the Royal Society in London on 26th to 28th September 2011. Computer and Information Sciences II contains novel advances in the state of the art covering applied research in electrical and computer engineering and computer science, across the broad area of information technology. It provides access to the main innovative activities in research across the world, and points to the results obtained recently by some of the most active teams in both Europe and Asia.