Visual perception is a complex process requiring interaction between the receptors in the eye that sense the stimulus and the neural system and the brain that are responsible for communicating and interpreting the sensed visual information. This process involves several physical, neural, and cognitive phenomena whose understanding is essential to design effective and computationally efficient imaging solutions. Building on advances in computer vision, image and video processing, neuroscience, and information engineering, perceptual digital imaging greatly enhances the capabilities of traditional imaging methods. Filling a gap in the literature, Perceptual Digital Imaging: Methods and Applications comprehensively covers the system design, implementation, and application aspects of this emerging specialized area. It gives readers a strong, fundamental understanding of theory and methods, providing a foundation on which solutions for many of the most interesting and challenging imaging problems can be built. The book features contributions by renowned experts who present the state of the art and recent trends in image acquisition, processing, storage, display, and visual quality evaluation. They detail advances in the field and explore human visual system-driven approaches across a broad spectrum of applications, including: Image quality and aesthetics assessment Digital camera imaging White balancing and color enhancement Thumbnail generation Image restoration Super-resolution imaging Digital halftoning and dithering Color feature extraction Semantic multimedia analysis and processing Video shot characterization Image and video encryption Display quality enhancement This is a valuable resource for readers who want to design and implement more effective solutions for cutting-edge digital imaging, computer vision, and multimedia applications. Suitable as a graduate-level textbook or stand-alone reference for researchers and practitioners, it provides a unique overview of an important and rapidly developing research field.

This edition presents the most prominent topics and applications of digital image processing, analysis, and computer graphics in the field of cultural heritage preservation. The text assumes prior knowledge of digital image processing and computer graphics fundamentals. Each chapter contains a table of contents, illustrations, and figures that elucidate the presented concepts in detail, as well as a chapter summary and a bibliography for further reading. Well-known experts cover a wide range of topics and related applications, including spectral imaging, automated restoration, computational reconstruction, digital reproduction, and 3D models.

Image 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.

In the development of digital multimedia, the importance and impact of image processing and mathematical morphology are well documented in areas ranging from automated vision detection and inspection to object recognition, image analysis and pattern recognition. Those working in these ever-evolving fields require a solid grasp of basic fundamentals, theory, and related applications-and few books can provide the unique tools for learning contained in this text. Image Processing and Mathematical Morphology: Fundamentals and Applications is a comprehensive, wide-ranging overview of morphological mechanisms and techniques and their relation to image processing. More than merely a tutorial on vital technical information, the book places this knowledge into a theoretical framework. This helps readers analyze key principles and architectures and then use the author's novel ideas on implementation of advanced algorithms to formulate a practical and detailed plan to develop and foster their own ideas. The book: Presents the history and state-of-the-art techniques related to image morphological processing, with numerous practical examples Gives readers a clear tutorial on complex technology and other tools that rely on their intuition for a clear understanding of the subject Includes an updated bibliography and useful graphs and illustrations Examines several new algorithms in great detail so that readers can adapt them to derive their own solution approaches This invaluable reference helps readers assess and simplify problems and their essential requirements and complexities, giving them all the necessary data and methodology to master current theoretical developments and applications, as well as create new ones.

Covering 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.

With rapid progress in Internet and digital imaging technology, there are more and more ways to easily create, publish, and distribute images. Considered the first book to focus on the relationship between digital imaging and privacy protection, Visual Cryptography and Secret Image Sharing is a complete introduction to novel security methods and sharing-control mechanisms used to protect against unauthorized data access and secure dissemination of sensitive information. Image data protection and image-based authentication techniques offer efficient solutions for controlling how private data and images are made available only to select people. Essential to the design of systems used to manage images that contain sensitive data-such as medical records, financial transactions, and electronic voting systems-the methods presented in this book are useful to counter traditional encryption techniques, which do not scale well and are less efficient when applied directly to image files. An exploration of the most prominent topics in digital imaging security, this book discusses: Potential for sharing multiple secrets Visual cryptography schemes-based either on the probabilistic reconstruction of the secret image, or on different logical operations for combining shared images Inclusion of pictures in the distributed shares Contrast enhancement techniques Color-image visual cryptography Cheating prevention Alignment problems for image shares Steganography and authentication In the continually evolving world of secure image sharing, a growing number of people are becoming involved as new applications and business models are being developed all the time. This contributed volume gives academicians, researchers, and professionals the insight of well-known experts on key concepts, issues, trends, and technologies in this emerging field.

The book has two intentions. First, it assembles the latest research in the field of medical imaging technology in one place. Detailed descriptions of current state-of-the-art medical imaging systems (comprised of x-ray CT, MRI, ultrasound, and nuclear medicine) and data processing techniques are discussed. Information is provided that will give interested engineers and scientists a solid foundation from which to build with additional resources. Secondly, it exposes the reader to myriad applications that medical imaging technology has enabled.

As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins with a section on standards, fundamental methods, design issues, and typical architectures. It then focuses on the coding of video and multimedia content before covering multimedia search, retrieval, and management. After examining multimedia security, the book describes multimedia communications and networking and explains the architecture design and implementation for multimedia image and video processing. It concludes with a section on multimedia systems and applications. Written by some of the most prominent experts in the field, this updated edition provides readers with the latest research in multimedia processing and equips them with advanced techniques for the design of multimedia systems.

This book encompasses a collection of topics covering recent advances that are important to the Arabic language in areas of natural language processing, speech and image analysis. This book presents state-of-the-art reviews and fundamentals as well as applications and recent innovations.The book chapters by top researchers present basic concepts and challenges for the Arabic language in linguistic processing, handwritten recognition, document analysis, text classification and speech processing. In addition, it reports on selected applications in sentiment analysis, annotation, text summarization, speech and font analysis, word recognition and spotting and question answering.Moreover, it highlights and introduces some novel applications in vital areas for the Arabic language. The book is therefore a useful resource for young researchers who are interested in the Arabic language and are still developing their fundamentals and skills in this area. It is also interesting for scientists who wish to keep track of the most recent research directions and advances in this area.

"John Russ is the master of explaining how image processing gets applied to real-world situations. With Brent Neal, he's done it again in Measuring Shape, this time explaining an expanded toolbox of techniques that includes useful, state-of-the-art methods that can be applied to the broad problem of understanding, characterizing, and measuring shape. He has a gift for finding the kernel of a particular algorithm, explaining it in simple terms, then giving concrete examples that are easily understood. His perspective comes from solving real-world problems and separating out what works in practice from what is just an abstract curiosity." -Tom Malzbender, Hewlett-Packard Laboratories, Palo Alto, California, USA Useful for those working in fields including industrial quality control, research, and security applications, Measuring Shape is a handbook for the practical application of shape measurement. Covering a wide range of shape measurements likely to be encountered in the literature and in software packages, this book presents an intentionally diverse set of examples that illustrate and enable readers to compare methods used for measurement and quantitative description of 2D and 3D shapes. It stands apart through its focus on examples and applications, which help readers quickly grasp the usefulness of presented techniques without having to approach them through the underlying mathematics. An elusive concept, shape is a principal governing factor in determining the behavior of objects and structures. Essential to recognizing and classifying objects, it is the central link in manmade and natural processes. Shape dictates everything from the stiffness of a construction beam, to the ability of a leaf to catch water, to the marketing and packaging of consumer products. This book emphasizes techniques that are quantitative and produce a meaningful yet compact set of numerical values that can be used for statistical analysis, comparison, correlation, classification, and identification. Written by two renowned authors from both industry and academia, this resource explains why users should select a particular method, rather than simply discussing how to use it. Showcasing each process in a clear, accessible, and well-organized way, they explore why a particular one might be appropriate in a given situation, yet a poor choice in another. Providing extensive examples, plus full mathematical descriptions of the various measurements involved, they detail the advantages and limitations of each method and explain the ways they can be implemented to discover important correlations between shape and object history or behavior. This uncommon assembly of information also includes sets of data on real-world objects that are used to compare the performance and utility of the various presented approaches.

- the book can be used by beginners in the field, tracking from basic principles to how to bend the rules, in reader-friendly language throughout - the book is based on a popular blog which dovetails as a fantastic companion website: https://questionsindataviz.com/ - the author is a very experienced and well-respected practitioner in the field, with a good-size following on social media: https://twitter.com/theneilrichards

This 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.

Providing specific knowledge in the theory of image analysis, optics, fluorescence, and imaging devices in biomedical laboratories, this timely and indispensable volume focuses on the theory and applications of detection, morphometry, and motility measurement techniques applied to bacteria, fungi, yeasts and protozoa.

It has long been a dream to realize machines with flexible visual perception capability. Research on digital image processing by computers was initiated about 30 years ago, and since then a wide variety of image processing algorithms have been devised. Using such image processing algorithms and advanced hardware technologies, many practical ma chines with visual recognition capability have been implemented and are used in various fields: optical character readers and design chart readers in offices, position-sensing and inspection systems in factories, computer tomography and medical X-ray and microscope examination systems in hospitals, and so on. Although these machines are useful for specific tasks, their capabilities are limited. That is, they can analyze only simple images which are recorded under very carefully adjusted photographic conditions: objects to be recognized are isolated against a uniform background and under well-controlled artificial lighting. In the late 1970s, many image understanding systems were de veloped to study the automatic interpretation of complex natural scenes. They introduced artificial intelligence techniques to represent the knowl edge about scenes and to realize flexible control structures. The first author developed an automatic aerial photograph interpretation system based on the blackboard model (Naga1980). Although these systems could analyze fairly complex scenes, their capabilities were still limited; the types of recognizable objects were limited and various recognition vii viii Preface errors occurred due to noise and the imperfection of segmentation algorithms."

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image. Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects. Learn: Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects Methods and theories for medical image recognition, segmentation and parsing of multiple objects Efficient and effective machine learning solutions based on big datasets Selected applications of medical image parsing using proven algorithms

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

This state-of-the-art set of handbooks provides medical physicists with a comprehensive overview of the field of nuclear medicine. In addition to describing the underlying, fundamental theories of the field, it includes the latest research and explores the practical procedures, equipment, and regulations that are shaping the field and it's future. This set is split into three volumes, respectively titled: Instrumentation and Imaging Procedures; Modelling, Dosimetry and Radiation Protection; and Radiopharmaceuticals and Clinical Applications. Volume one, Instrumentation and Imaging Procedures, focuses primarily on providing a comprehensive review into the detection of radiation, beginning with an introduction to the history of nuclear medicine to the latest imaging technology. Volume two, Modelling, Dosimetry and Radiation Protection, explores the applications of mathematical modelling, dosimetry, and radiation protection in nuclear medicine. The third and final volume, Radiopharmaceuticals and Clinical Applications, highlights the production and application of radiopharmaceuticals and their role in clinical nuclear medicine practice. These books will be an invaluable resource for libraries, institutions, and clinical and academic medical physicists searching for a complete account of what defines nuclear medicine. The most comprehensive reference available providing a state-of-the-art overview of the field of nuclear medicine Edited by a leader in the field, with contributions from a team of experienced medical physicists, chemists, engineers, scientists, and clinical medical personnel Includes the latest practical research in the field, in addition to explaining fundamental theory and the field's history

A Unique, Cutting-Edge Approach to Optical Filter Design With more and more information being transmitted over fiber-optic lines, optical filtering has become crucial to the advanced functionality of today’s communications networks. Helping researchers and engineers keep pace with this rapidly evolving technology, this book presents digital processing techniques for optical filter design. This higher-level approach focuses on filter characteristics and enables readers to quickly calculate the filter response as well as tackle larger and more complex filters. The authors incorporate numerous theoretical and experimental results from the literature and discuss applications to a variety of systems—including the new wavelength division multiplexing (WDM) technology, which is fast becoming the preferred method for system upgrade and expansion. Special features of this book include:

• The theory underlying various architectures that can approximate any filter function
• Filter design techniques applicable to a broad range of materials systems—from silica to fiber to microelectromechanical (MEM) systems
• Design examples relevant to filters for WDM systems and planar waveguide devices
• 250 figures as well as problem sets for use in graduate-level studies

This book introduces the fundamental concepts of modern digital image processing. It aims to help the students, scientists, and practitioners to understand the concepts through clear explanations, illustrations and examples. The discussion of the general concepts is supplemented with examples from applications and ready-to-use implementations of concepts in MATLAB®. Program code of some important concepts in programming language 'C' is provided.

To explain the concepts, MATLAB® functions are used throughout the book. MATLAB® Version 9.3 (R2017b), Image Acquisition Toolbox Version 5.3 (R2017b), Image Processing Toolbox, Version 10.1 (R2017b) have been used to create the book material.

Meant for students and practicing engineers, this book provides a clear, comprehensive and up-to-date introduction to Digital Image Processing in a pragmatic manner.

Table of Contents

Introduction to Digital Image Processing. Digital Image representation. Mathematical Tools for Image Processing. Image Enhancement in Spatial Domain. Image Processing in Frequency Domain. Image Denoising. Image Segmentation. Mathematical Morphology. Image Understanding. Image Compression. Image Retrieval. Digital Image Forgery. Appendix A. Appendix B. Appendix B.

The arrival of the digital age has created the need to be able to store, manage, and digitally use an ever-increasing amount of video and audio material. Thus, video cataloguing has emerged as a requirement of the times. Video Cataloguing: Structure Parsing and Content Extraction explains how to efficiently perform video structure analysis as well as extract the basic semantic contents for video summarization, which is essential for handling large-scale video data. This book addresses the issues of video cataloguing, including video structure parsing and basic semantic word extraction, particularly for movie and teleplay videos. It starts by providing readers with a fundamental understanding of video structure parsing. It examines video shot boundary detection, recent research on video scene detection, and basic ideas for semantic word extraction, including video text recognition, scene recognition, and character identification. The book lists and introduces some of the most commonly used features in video analysis. It introduces and analyzes the most popular shot boundary detection methods and also presents recent research on movie scene detection as another important and critical step for video cataloguing, video indexing, and retrieval. The authors propose a robust movie scene recognition approach based on a panoramic frame and representative feature patch. They describe how to recognize characters in movies and TV series accurately and efficiently as well as how to use these character names as cataloguing items for an intelligent catalogue. The book proposes an interesting application of highlight extraction in basketball videos and concludes by demonstrating how to design and implement a prototype system of automatic movie and teleplay cataloguing (AMTC) based on the approaches introduced in the book.

In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book. Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally. The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization. Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling.

A timely and authoritative guide to the state of the art of wave scattering

Scattering of Electromagnetic Waves offers in three volumes a complete and up-to-date treatment of wave scattering by random discrete scatterers and rough surfaces. Written by leading scientists who have made important contributions to wave scattering over three decades, this new work explains the principles, methods, and applications of this rapidly expanding, interdisciplinary field. It covers both introductory and advanced material and provides students and researchers in remote sensing as well as imaging, optics, and electromagnetic theory with a one-stop reference to a wealth of current research results. Plus, Scattering of Electromagnetic Waves contains detailed discussions of both analytical and numerical methods, including cutting-edge techniques for the recovery of earth/land parametric information.

The three volumes are entitled respectively Theories and Applications, Numerical Simulation, and Advanced Topics. In the first volume, Theories and Applications, Leung Tsang (University of Washington) Jin Au Kong (MIT), and Kung-Hau Ding (Air Force Research Lab) cover:

• Basic theory of electromagnetic scattering
• Fundamentals of random scattering
• Characteristics of discrete scatterers and rough surfaces
• Scattering and emission by layered media
• Single scattering and applications
• Radiative transfer theory and solution techniques
• One-dimensional random rough surface scattering

As science becomes increasingly computational, the limits of what is computationally tractable become a barrier to scientific progress. Many scientific problems, however, are amenable to human problem solving skills that complement computational power. By leveraging these skills on a larger scale - beyond the relatively few individuals currently engaged in scientific inquiry - there is the potential for new scientific discoveries. This book presents a framework for mapping open scientific problems into video games. The game framework combines computational power with human problem solving and creativity to work toward solving scientific problems that neither computers nor humans could previously solve alone. To maximize the potential contributors to scientific discovery, the framework designs a game to be played by people with no formal scientific background and incentivizes long- term engagement with a myriad of collaborative on competitive reward structures. The framework allows for the continual coevolution of the players and the game to each other: as players gain expertise through gameplay, the game changes to become a better tool. The framework is validated by being applied to proteomics problems with the video game Foldit. Foldit players have contributed to novel discoveries in protein structure prediction, protein design, and protein structure refinement algorithms. The coevolution of human problem solving and computer tools in an incentivized game framework is an exciting new scientific pathway that can lead to discoveries currently unreachable by other methods.

This interdisciplinary study participates in the ongoing critical conversation about postwar American poetry and visual culture, while advancing that field into the arena of the museum. Turning to contemporary poems about the visual arts that foreground and interrogate a museum setting, the book demonstrates the particular importance of the museum as a cultural site that is both inspiration and provocation for poets. The study uniquely bridges the "dual canon" in contemporary poetry (and calls the lyric/avant-garde distinction into question) by analyzing museum-sponsored anthologies as well as poems by John Ashbery, Richard Howard, Kenneth Koch, Kathleen Fraser, Cole Swensen, Anne Carson, and others. Through these case studies of poets with diverse affiliations, the author shows that the boom in ekphrasis in the past 20 years is not only an aesthetic but a critical phenomenon, a way that poets have come to terms with the critical dilemmas of our moment. Highlighting the importance of poets' "peripheral vision"-awareness of the institutional conditions that frame encounters with art-the author contend that a museum visit becomes a forum for questioning oppositions that have preoccupied literary criticism for the past 50 years: homage and innovation, modernism and postmodernism, subjectivity and collectivity. The study shows that ekphrasis becomes a strategy for negotiating these impasses-a mode of political inquiry, a meditation on canonization, a venue for comic appraisal of institutionalization, and a means of "site-specific" feminist revision-in a vital synthesis of critique, perspicacity, and pleasure.

The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting. Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration. This volume starts with a wide review on image denoising, retracing and comparing various methods from the pioneer signal processing methods, to machine learning approaches with sparse and low-rank models, and recent deep learning architectures with autoencoders and variants. The following chapters present results from the Challenge, including three competition tasks at WCCI and ECML 2018. The top best approaches submitted by participants are described, showing interesting contributions and innovating methods. The last two chapters propose novel contributions and highlight new applications that benefit from image/video inpainting.