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Image Making in Byzantium, Sasanian Persia and the Early Muslim World: Images and Cultures (Variorum Collected Studies #905)
by Anthony CutlerRelations between Byzantium and its neighbours are the focus of this volume. The papers address questions of cultural exchange, with special attention to art historical relations as shown by technical, iconographic and diplomatic exchanges. While addressed to specialists, both their approach and the language make these papers accessible to students at all levels.
Image Matters: Archive, Photography, and the African Diaspora in Europe
by Tina M. CamptIn Image Matters, Tina M. Campt traces the emergence of a black European subject by examining how specific black European communities used family photography to create forms of identification and community. At the heart of Campt's study are two photographic archives, one composed primarily of snapshots of black German families taken between 1900 and 1945, and the other assembled from studio portraits of West Indian migrants to Birmingham, England, taken between 1948 and 1960. Campt shows how these photographs conveyed profound aspirations to forms of national and cultural belonging. In the process, she engages a host of contemporary issues, including the recoverability of non-stereotypical life stories of black people, especially in Europe, and their impact on our understanding of difference within diaspora; the relevance and theoretical approachability of domestic, vernacular photography; and the relationship between affect and photography. Campt places special emphasis on the tactile and sonic registers of family photographs, and she uses them to read the complexity of "race" in visual signs and to highlight the inseparability of gender and sexuality from any analysis of race and class. Image Matters is an extraordinary reflection on what vernacular photography enabled black Europeans to say about themselves and their communities.
Image Objects: An Archaeology of Computer Graphics
by Jacob GabouryHow computer graphics transformed the computer from a calculating machine into an interactive medium, as seen through the histories of five technical objects.Most of us think of computer graphics as a relatively recent invention, enabling the spectacular visual effects and lifelike simulations we see in current films, television shows, and digital games. In fact, computer graphics have been around as long as the modern computer itself, and played a fundamental role in the development of our contemporary culture of computing. In Image Objects, Jacob Gaboury offers a prehistory of computer graphics through an examination of five technical objects--an algorithm, an interface, an object standard, a programming paradigm, and a hardware platform--arguing that computer graphics transformed the computer from a calculating machine into an interactive medium. Gaboury explores early efforts to produce an algorithmic solution for the calculation of object visibility; considers the history of the computer screen and the random-access memory that first made interactive images possible; examines the standardization of graphical objects through the Utah teapot, the most famous graphical model in the history of the field; reviews the graphical origins of the object-oriented programming paradigm; and, finally, considers the development of the graphics processing unit as the catalyst that enabled an explosion in graphical computing at the end of the twentieth century. The development of computer graphics, Gaboury argues, signals a change not only in the way we make images but also in the way we mediate our world through the computer--and how we have come to reimagine that world as computational.
Image Processing Recipes in MATLAB® (Chapman & Hall/CRC Computer Science and Engineering Recipes Series)
by Oge Marques Gustavo Benvenutti BorbaLeveraging the latest developments in MATLAB and its image processing toolbox, this 'cookbook' is a collection of 30 practical recipes for image processing, ranging from foundational techniques to recently published algorithms. Presented in a clear and meaningful sequence, these recipes are prepared with the reader in mind, allowing one to focus on particular topics or read as a whole from cover to cover.Key Features: A practical, user-friendly guide that equips researchers and practitioners with the tools to implement efficient image processing workflows in MATLAB. Each recipe is presented through clear, step-by-step instructions and rich visual examples. Each recipe contains its own source code, explanations, and figures, making the book an excellent standalone resource for quick reference. Strategically structured to aid sequential learning, yet with self-contained chapters for those seeking solutions to specific image processing challenges. The book serves as a concise and readable practical reference to deploy image processing pipelines in MATLAB quickly and efficiently. With its accessible and practical approach, the book is a valuable guide for those who navigate this evolving area, including researchers, students, developers, and practitioners in the fields of image processing, computer vision, and image analysis.
Image Processing and Analysis with Graphs: Theory and Practice (Digital Imaging and Computer Vision #5)
by OLIVER LÉZORAY AND LEO GRADYCovering the theoretical aspects of image processing and analysis through the use of graphs in the representation and analysis of objects, Image Processing and Analysis with Graphs: Theory and Practice also demonstrates how these concepts are indispensible for the design of cutting-edge solutions for real-world applications. Explores new applications in computational photography, image and video processing, computer graphics, recognition, medical and biomedical imaging With the explosive growth in image production, in everything from digital photographs to medical scans, there has been a drastic increase in the number of applications based on digital images. This book explores how graphs—which are suitable to represent any discrete data by modeling neighborhood relationships—have emerged as the perfect unified tool to represent, process, and analyze images. It also explains why graphs are ideal for defining graph-theoretical algorithms that enable the processing of functions, making it possible to draw on the rich literature of combinatorial optimization to produce highly efficient solutions. Some key subjects covered in the book include: Definition of graph-theoretical algorithms that enable denoising and image enhancement Energy minimization and modeling of pixel-labeling problems with graph cuts and Markov Random Fields Image processing with graphs: targeted segmentation, partial differential equations, mathematical morphology, and wavelets Analysis of the similarity between objects with graph matching Adaptation and use of graph-theoretical algorithms for specific imaging applications in computational photography, computer vision, and medical and biomedical imaging Use of graphs has become very influential in computer science and has led to many applications in denoising, enhancement, restoration, and object extraction. Accounting for the wide variety of problems being solved with graphs in image processing and computer vision, this book is a contributed volume of chapters written by renowned experts who address specific techniques or applications. This state-of-the-art overview provides application examples that illustrate practical application of theoretical algorithms. Useful as a support for graduate courses in image processing and computer vision, it is also perfect as a reference for practicing engineers working on development and implementation of image processing and analysis algorithms.
Image Processing and Capsule Networks: ICIPCN 2020 (Advances in Intelligent Systems and Computing #1200)
by João Manuel R. S. Tavares Joy Iong-Zong Chen Subarna Shakya Abdullah M. IliyasuThis book emphasizes the emerging building block of image processing domain, which is known as capsule networks for performing deep image recognition and processing for next-generation imaging science. Recent years have witnessed the continuous development of technologies and methodologies related to image processing, analysis and 3D modeling which have been implemented in the field of computer and image vision. The significant development of these technologies has led to an efficient solution called capsule networks [CapsNet] to solve the intricate challenges in recognizing complex image poses, visual tasks, and object deformation. Moreover, the breakneck growth of computation complexities and computing efficiency has initiated the significant developments of the effective and sophisticated capsule network algorithms and artificial intelligence [AI] tools into existence. The main contribution of this book is to explain and summarize the significant state-of-the-art research advances in the areas of capsule network [CapsNet] algorithms and architectures with real-time implications in the areas of image detection, remote sensing, biomedical image analysis, computer communications, machine vision, Internet of things, and data analytics techniques.
Image Processing and Communications: Techniques, Algorithms and Applications (Advances in Intelligent Systems and Computing #1062)
by Ryszard S. Choraś Michał ChoraśThis book presents a selection of high-quality peer-reviewed research papers on various aspects of computer science and networks. It not only discusses emerging applications of currently available solutions, but also outlines potential future techniques and lines of research in pattern recognition, image processing and communications. Given its scope, the book will be of considerable interest to researchers, students and practitioners alike. All papers gathered here were presented at the Image Processing and Communications Conference, held in Bydgoszcz, Poland on September 11–13, 2019.
Image Processing and Computer Vision in iOS (SpringerBriefs in Computer Science)
by Oge MarquesThis book presents the fundamentals of mobile visual computing in iOS development and provides directions for developers and researchers interested in developing iOS applications with image processing and computer vision capabilities. Presenting a technical overview of some of the tools, languages, libraries, frameworks, and APIs currently available for developing iOS applications Image Processing and Computer Vision in iOS reveals the rich capabilities in image processing and computer vision. Its main goal is to provide a road map to what is currently available, and a path to successfully tackle this rather complex but highly rewarding task.
Image Processing and Machine Learning, Volume 1: Foundations of Image Processing
by Erik Cuevas Alma Nayeli RodríguezImage processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. It provides a solid foundation for readers interested in understanding the core principles and practical applications of image processing, establishing the essential groundwork necessary for further explorations covered in Volume 2. Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.
Image Processing for Cinema (Chapman & Hall/CRC Mathematical and Computational Imaging Sciences Series)
by Marcelo BertalmioImage Processing for Cinema presents a detailed overview of image processing techniques that are used in practice in digital cinema. The book shows how image processing has become ubiquitous in movie-making, from shooting to exhibition. It covers all the ways in which image processing algorithms are used to enhance, restore, adapt, and convert movi
Image Processing using Pulse-Coupled Neural Networks: Applications in Python
by Thomas Lindblad Jason M. KinserImage processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.
Image Processing with ImageJ
by Javier Pascau Jose Maria Mateos-PerezThe book will help readers discover the various facilities of ImageJ through a tutorial-based approach.This book is targeted at scientists, engineers, technicians, and managers, and anyone who wishes to master ImageJ for image viewing, processing, and analysis. If you are a developer, you will be able to code your own routines after you have finished reading this book. No prior knowledge of ImageJ is expected.
Image Processing with MATLAB: Applications in Medicine and Biology
by Omer Demirkaya Musa H. Asyali Prasanna K. SahooImage Processing with MATLAB: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLAB algorithms. It describes classical as well emerging areas in image processing and analysis. Providing many unique MATLAB codes and functions throughout, the book covers the theory of probability an
Image Processing: Dealing with Texture
by Maria M. Petrou Sei-ichiro KamataThe classic text that covers practical image processing methods and theory for image texture analysis, updated second edition The revised second edition of Image Processing: Dealing with Textures updates the classic work on texture analysis theory and methods without abandoning the foundational essentials of this landmark work. Like the first, the new edition offers an analysis of texture in digital images that are essential to a diverse range of applications such as: robotics, defense, medicine and the geo-sciences. Designed to easily locate information on specific problems, the text is structured around a series of helpful questions and answers. Updated to include the most recent developments in the field, many chapters have been completely revised including: Fractals and Multifractals, Image Statistics, Texture Repair, Local Phase Features, Dual Tree Complex Wavelet Transform, Ridgelets and Curvelets and Deep Texture Features. The book takes a two-level mathematical approach: light math is covered in the main level of the book, with harder math identified in separate boxes. This important text: Contains an update of the classic advanced text that reviews practical image processing methods and theory for image texture analysis Puts the focus exclusively on an in-depth exploration of texture Contains a companion website with exercises and algorithms Includes examples that are fully worked to enhance the learning experience Written for students and researchers of image processing, the second edition of Image Processing has been revised and updated to incorporate the foundational information on the topic and information on the latest advances.
Image Registration
by A. Ardeshir GoshtasbyThis book presents a thorough and detailed guide to image registration, outlining the principles and reviewing state-of-the-art tools and methods. The book begins by identifying the components of a general image registration system, and then describes the design of each component using various image analysis tools. The text reviews a vast array of tools and methods, not only describing the principles behind each tool and method, but also measuring and comparing their performances using synthetic and real data. Features: discusses similarity/dissimilarity measures, point detectors, feature extraction/selection and homogeneous/heterogeneous descriptors; examines robust estimators, point pattern matching algorithms, transformation functions, and image resampling and blending; covers principal axes methods, hierarchical methods, optimization-based methods, edge-based methods, model-based methods, and adaptive methods; includes a glossary, an extensive list of references, and an appendix on PCA.
Image Restoration: Fundamentals and Advances (Digital Imaging and Computer Vision #7)
by Xin Li Bahadir K. GunturkImage Restoration: Fundamentals and Advances responds to the need to update most existing references on the subject, many of which were published decades ago. Providing a broad overview of image restoration, this book explores breakthroughs in related algorithm development and their role in supporting real-world applications associated with various scientific and engineering fields. These include astronomical imaging, photo editing, and medical imaging, to name just a few. The book examines how such advances can also lead to novel insights into the fundamental properties of image sources. Addressing the many advances in imaging, computing, and communications technologies, this reference strikes just the right balance of coverage between core fundamental principles and the latest developments in this area. Its content was designed based on the idea that the reproducibility of published works on algorithms makes it easier for researchers to build on each other’s work, which often benefits the vitality of the technical community as a whole. For that reason, this book is as experimentally reproducible as possible. Topics covered include: Image denoising and deblurring Different image restoration methods and recent advances such as nonlocality and sparsity Blind restoration under space-varying blur Super-resolution restoration Learning-based methods Multi-spectral and color image restoration New possibilities using hybrid imaging systems Many existing references are scattered throughout the literature, and there is a significant gap between the cutting edge in image restoration and what we can learn from standard image processing textbooks. To fill that need but avoid a rehash of the many fine existing books on this subject, this reference focuses on algorithms rather than theories or applications. Giving readers access to a large amount of downloadable source code, the book illustrates fundamental techniques, key ideas developed over the years, and the state of the art in image restoration. It is a valuable resource for readers at all levels of understanding.
Image Science: Iconology, Visual Culture, and Media Aesthetics
by W.J.T. MitchellAlmost thirty years ago, W. J. T. Mitchell's Iconology helped launch the interdisciplinary study of visual media, now a central feature of the humanities. Along with his subsequent Picture Theory and What Do Pictures Want?, Mitchell's now-classic work introduced such ideas as the pictorial turn, the image/picture distinction, the metapicture, and the biopicture. These key concepts imply an approach to images as true objects of investigation--an "image science. " Continuing with this influential line of thought, Image Science gathers Mitchell's most recent essays on media aesthetics, visual culture, and artistic symbolism. The chapters delve into such topics as the physics and biology of images, digital photography and realism, architecture and new media, and the occupation of space in contemporary popular uprisings. The book looks both backward at the emergence of iconology as a field and forward toward what might be possible if image science can indeed approach pictures the same way that empirical sciences approach natural phenomena. Essential for those involved with any aspect of visual media, Image Science is a brilliant call for a method of studying images that overcomes the "two-culture split" between the natural and human sciences.
Image Statistics in Visual Computing
by Tania Pouli Erik Reinhard Douglas W. CunninghamTo achieve the complex task of interpreting what we see, our brains rely on statistical regularities and patterns in visual data. Knowledge of these regularities can also be considerably useful in visual computing disciplines, such as computer vision, computer graphics, and image processing. The field of natural image statistics studies the regular
Image Studies: Theory and Practice
by Sunil ManghaniImage Studies offers an engaging introduction to visual and image studies. In order to better understand images and visual culture the book seeks to bridge between theory and practice; asking the reader to think critically about images and image practices, but also simultaneously to make images and engage with image-makers and image-making processes. Looking across a range of domains and disciplines, we find the image is never a single, static thing. Rather, the image can be a concept, an object, a picture, or medium – and all these things combined. At the heart of this book is the idea of an ‘ecology of images’, through which we can examine the full ‘life’ of an image – to understand how an image resonates within a complex set of contexts, processes and uses. Part 1 covers theoretical perspectives on the image, supplemented with practical entries on making, researching and writing with images. Part 2 explores specific image practices and cultures, with chapters on drawing and painting; photography; visual culture; scientific imaging; and informational images. A wide range of illustrations complement the text throughout and each chapter includes creative tasks, keywords (linked to an online resource), summaries and suggested further reading. In addition, each of the main chapters include selected readings by notable authors across a range of subject areas, including: Art History, Business, Cognitive Science, Communication Studies, Infographics, Neuroscience, Photography, Physics, Science Studies, Social Semiotics, Statistics, and Visual Culture.
Image Super-Resolution and Applications
by Fathi E. El-Samie Mohiy M. Hadhoud Said E. El-KhamyThis book is devoted to the issue of image super-resolution-obtaining high-resolution images from single or multiple low-resolution images. Although there are numerous algorithms available for image interpolation and super-resolution, there's been a need for a book that establishes a common thread between the two processes. Filling this need, Image
Image Texture Analysis: Foundations, Models and Algorithms
by Chih-Cheng Hung Enmin Song Yihua LanThis useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.
Image and Concept: Mythopoetic Roots of Literature
by Olga FreidenbergFirst published in 1997. Routledge is an imprint of Taylor & Francis, an informa company.
Image and Graphics
by Yu-Jin ZhangThis book constitutes the refereed conference proceedings of the 8th International Conference on Image and Graphics, ICIG 2015 held in Tianjin, China, in August 2015. The 164 revised full papers and 6 special issue papers were carefully reviewed and selected from 339 submissions. The papers focus on various advances of theory, techniques and algorithms in the fields of images and graphics.
Image and Graphics Technologies and Applications: 13th Conference On Image And Graphics Technologies And Applications, Igta 2018, Beijing, China, April 8-10, 2018, Revised Selected Papers (Communications In Computer And Information Science #875)
by Yongtian Wang Zhiguo Jiang Yuxin PengThis book constitutes the refereed proceedings of the 13th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2018, held in Beijing, China in April, 2018. The 64 papers presented were carefully reviewed and selected from 138 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR; as well as image technology applications.
Image and Graphics Technologies and Applications: 14th Conference on Image and Graphics Technologies and Applications, IGTA 2019, Beijing, China, April 19–20, 2019, Revised Selected Papers (Communications in Computer and Information Science #1043)
by Yongtian Wang Yuxin Peng Qingmin HuangThis book constitutes the refereed proceedings of the 14th Conference on Image and Graphics Technologies and Applications, IGTA 2019, held in Beijing, China in April, 2019. The 66 papers presented were carefully reviewed and selected from 152 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR, as well as image technology applications.