Psychoanalysis and the Image

With contributions from leading European and American psychoanalysts, this innovative text systematically investigates and analyses the relationship between clinical practice and psychoanalytic theories. It examines clinical practice experience in detail and links it with the knowledge gained from official theory. To make this type of analysis of clinical material possible, the team of authors have devised a grid called The Map. This new instrument details the implicit theories of the analyst at work and can be used in everyday clinical work and supervisions. These analyses highlight the divergences and convergences with theory, but also reveal outlines for new models. Psychoanalysis: From Practice to Theory makes a significant contribution to the debate about the most important problems that psychoanalysis presents. It will be of great value to psychoanalysts, psychotherapists, and students of psychoanalysis. Contributors: Jorge L. Ahumada, Werner Bohleber, Jorge Canestri, Paul Denis, Peter Fonagy, William I. Grossman, Gail S. Reed, David Tuckett, Samuel Zysman Whurr Series in Psychoanalysis Edited by Peter Fonagy and Mary Target

This concise companion explores the history of psychoanalytic theory and its impact on contemporary literary criticism by tracing its movement across disciplinary and cultural boundaries. Contains original essays by leading scholars, using a wide range of cultural and historical approaches Discusses key concepts in psychoanalysis, such as the role of dreaming, psychosexuality, the unconscious, and the figure of the double, while considering questions of gender, race, asylum and international law, queer theory, time, and memory Spans the fields of psychoanalysis, literature, cultural theory, feminist and gender studies, translation studies, and film. Provides a timely and pertinent assessment of current psychoanalytic methods while also sketching out future directions for theory and interpretation

Digital practices are shaped by graphical representations that appear on the computer screen, which is the principal surface for designing, visualizing, and interacting with digital information. Before any digital image or graphical interface is rendered on the screen there is a series of layers that affect its visual properties. To discover such processes it is necessary to investigate software applications, graphical user interfaces, programming languages and code, algorithms, data structures, and data types in their relationship with graphical outcomes and design possibilities. This book studies interfaces as images and images as interfaces. It offers a comprehensible framework to study graphical representations of visual information. It explores the relationship between visual information and its graphical supports, taking into account contributions from fields of visual computing. Graphical supports are considered as material but also as formal aspects underlying the representation of digital images on the digital screen.

In recent years, Moore's law has fostered the steady growth of the field of digital image processing, though the computational complexity remains a problem for most of the digital image processing applications. In parallel, the research domain of optical image processing has matured, potentially bypassing the problems digital approaches were suffering and bringing new applications. The advancement of technology calls for applications and knowledge at the intersection of both areas but there is a clear knowledge gap between the digital signal processing and the optical processing communities. This book covers the fundamental basis of the optical and image processing techniques by integrating contributions from both optical and digital research communities to solve current application bottlenecks, and give rise to new applications and solutions. Besides focusing on joint research, it also aims at disseminating the knowledge existing in both domains. Applications covered include image restoration, medical imaging, surveillance, holography, etc… «a very good book that deserves to be on the bookshelf of a serious student or scientist working in these areas.» Source: Optics and Photonics News

The new, completely updated edition of the aerial photography classic Extensively revised to address today's technological advances, Aerial Photography and Image Interpretation, Third Edition offers a thorough survey of the technology, techniques, processes, and methods used to create and interpret aerial photographs. The new edition also covers other forms of remote sensing with topics that include the most current information on orthophotography (including digital), soft copy photogrammetry, digital image capture and interpretation, GPS, GIS, small format aerial photography, statistical analysis and thematic mapping errors, and more. A basic introduction is also given to nonphotographic and space-based imaging platforms and sensors, including Landsat, lidar, thermal, and multispectral. This new Third Edition features: Additional coverage of the specialized camera equipment used in aerial photography A strong focus on aerial photography and image interpretation, allowing for a much more thorough presentation of the techniques, processes, and methods than is possible in the broader remote sensing texts currently available Straightforward, user-friendly writing style Expanded coverage of digital photography Test questions and summaries for quick review at the end of each chapter Written in a straightforward style supplemented with hundreds of photographs and illustrations, Aerial Photography and Image Interpretation, Third Edition is the most in-depth resource for undergraduate students and professionals in such fields as forestry, geography, environmental science, archaeology, resource management, surveying, civil and environmental engineering, natural resources, and agriculture.

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.

Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc. This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing the technique with encoding, feature extraction, compressive sensing, multifractal analysis and texture analysis. It is aimed at industrial engineers, medical researchers, university lab attendants, lecturer-researchers and researchers from various specializations. It is also intended to contribute to the studies of graduate students in engineering, particularly in the fields of medical imaging, intelligent instrumentation, telecommunications, and signal and image processing. Given the diversity of the problems posed and addressed, this book paves the way for the development of new research themes, such as brain–computer interface (BCI), compressive sensing, functional magnetic resonance imaging (fMRI), tissue characterization (bones, skin, etc.) and the analysis of complex phenomena in general. Throughout the chapters, informative illustrations assist the uninitiated reader in better conceptualizing certain concepts, taking the form of numerous figures and recent applications in biomedical engineering, communication, multimedia, finance, etc.

A hands-on guide to image registration theory and methods—with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods. It provides in-depth exploration of an array of fundamental issues, including image orientation detection, similarity measures, feature extraction methods, and elastic transformation functions. Also covered are robust parameter estimation, validation methods, multi-temporal and multi-modality image registration, methods for determining the orientation of an image, methods for identifying locally unique neighborhoods in an image, methods for detecting lines in an image, methods for finding corresponding points and corresponding lines in images, registration of video images to create panoramas, and much more. Theory and Applications of Image Registration provides readers with a practical guide to the theory and underpinning principles. Throughout the book numerous real-world examples are given, illustrating how image registration can be applied to problems in various fields, including biomedicine, remote sensing, and computer vision. Also provided are software routines to help readers develop their image registration skills. Many of the algorithms described in the book have been implemented, and the software packages are made available to the readers of the book on a companion website. In addition, the book: Explores the fundamentals of image registration and provides a comprehensive look at its multi-disciplinary applications Reviews real-world applications of image registration in the fields of biomedical imaging, remote sensing, computer vision, and more Discusses methods in the registration of long videos in target tracking and 3-D reconstruction Addresses key research topics and explores potential solutions to a number of open problems in image registration Includes a companion website featuring fully implemented algorithms and image registration software for hands-on learning Theory and Applications of Image Registration is a valuable resource for researchers and professionals working in industry and government agencies where image registration techniques are routinely employed. It is also an excellent supplementary text for graduate students in computer science, electrical engineering, software engineering, and medical physics.

The first text to bridge the gap between image processing and jump regression analysis Recent statistical tools developed to estimate jump curves and surfaces have broad applications, specifically in the area of image processing. Often, significant differences in technical terminologies make communication between the disciplines of image processing and jump regression analysis difficult. In easy-to-understand language, Image Processing and Jump Regression Analysis builds a bridge between the worlds of computer graphics and statistics by addressing both the connections and the differences between these two disciplines. The author provides a systematic analysis of the methodology behind nonparametric jump regression analysis by outlining procedures that are easy to use, simple to compute, and have proven statistical theory behind them. Key topics include: Conventional smoothing procedures Estimation of jump regression curves Estimation of jump location curves of regression surfaces Jump-preserving surface reconstruction based on local smoothing Edge detection in image processing Edge-preserving image restoration With mathematical proofs kept to a minimum, this book is uniquely accessible to a broad readership. It may be used as a primary text in nonparametric regression analysis and image processing as well as a reference guide for academicians and industry professionals focused on image processing or curve/surface estimation.