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This book covers speckle image formation using a variety of modulated apertures. The central theme revolves around theoretical analyses, specifically the calculation of impulse responses or Point Spread Functions (PSFs) corresponding to these apertures. These calculations provide crucial insights into the resolution inherent in the resulting speckle images. The book begins with an examination of the recognition of the direction of new apertures from elongated speckle images, setting the stage for subsequent discussions. The theoretical analyses extend to diverse aperture designs, including Gaussian, graded-index, and modulated apertures. The book delves into the nuanced dynamics of contrast in speckle images, exploring the Voigt distribution and the effects of modulation on contrast. In addition to aperture-centric discussions, the book addresses the processing of the formed speckle images. The chapters impart a comprehensive understanding of speckle imaging, encompassing discrimination in microscopy using digital speckle images, the utilization of concentric hexagonal pupils, and the exploration of irregular apertures. The book culminates in a detailed exploration of speckle imaging in the context of an annular Hermite Gaussian laser beam. Overall, this book serves as a valuable resource for researchers and academics seeking a profound exploration of speckle image formation, modulation, and processing across a spectrum of apertures and theoretical frameworks.

In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book: Provides broad background on various image thresholding and segmentation techniques Discusses information on various assessment metrics and the confusion matrix Proposes integration of the thresholding technique with the bio-inspired algorithms Explores case studies including MRI, CT, dermoscopy, and ultrasound images Includes separate chapters on machine learning and deep learning for medical image processing

This much-needed text brings the treatment of optical pattern recognition up-to-date in one comprehensive resource. Optical pattern recognition, one of the first implementations of Fourier Optics, is now widely used, and this text provides an accessible introduction for readers who wish to get to grips with how holography is applied in a practical context. A wide range of devices are addressed from a user perspective and are accompanied with detailed tables enabling performance comparison, in addition to chapters exploring computer-generated holograms, optical correlator systems, and pattern matching algorithms. This book will appeal to both lecturers and research scientists in the field of electro-optic devices and systems. Features: Covers a range of new developments, including computer-generated holography and 3D image recognition Accessible without a range of prior knowledge, providing a clear exposition of technically difficult concepts Contains extensive examples throughout to reinforce learning

The Encyclopedia of Image Processing presents a vast collection of well-written articles covering image processing fundamentals (e.g. color theory, fuzzy sets, cryptography) and applications (e.g. geographic information systems, traffic analysis, forgery detection). Image processing advances have enabled many applications in healthcare, avionics, robotics, natural resource discovery, and defense, which makes this text a key asset for both academic and industrial libraries and applied scientists and engineers working in any field that utilizes image processing. Written by experts from both academia and industry, it is structured using the ACM Computing Classification System (CCS) first published in 1988, but most recently updated in 2012.

The book familiarizes readers with fundamental concepts and issues related to computer vision and major approaches that address them. The focus of the book is on image acquisition and image formation models, radiometric models of image formation, image formation in the camera, image processing concepts, concept of feature extraction and feature selection for pattern classification/recognition, and advanced concepts like object classification, object tracking, image-based rendering, and image registration. Intended to be a companion to a typical teaching course on computer vision, the book takes a problem-solving approach.

Sea Ice Image Processing with MATLAB addresses the topic of image processing for the extraction of key sea ice characteristics from digital photography, which is of great relevance for Artic remote sensing and marine operations. This valuable guide provides tools for quantifying the ice environment that needs to be identified and reproduced for such testing. This includes fit-for-purpose studies of existing vessels, new-build conceptual design and detailed engineering design studies for new developments, and studies of demanding marine operations involving multiple vessels and operational scenarios in sea ice. A major contribution of this work is the development of automated computer algorithms for efficient image analysis. These are used to process individual sea-ice images and video streams of images to extract parameters such as ice floe size distribution, and ice types. Readers are supplied with Matlab source codes of the algorithms for the image processing methods discussed in the book made available as online material. FeaturesPresents the first systematic work using image processing techniques to identify ice floe size distribution from aerial imagesHelps identify individual ice floe and obtain floe size distributions for Arctic offshore operations and transportationExplains specific algorithms that can be combined to solve various problems during polar sea ice investigationsIncludes MATLAB® codes useful not only for academics, but for ice engineers and scientists to develop tools applicable in different areas such as sustainable arctic marine and coastal technology researchProvides image processing techniques applicable to other fields like biomedicine, material science, etc

Today, remote sensing technology is an essential tool for understanding the Earth and managing human-Earth interactions. There is a rapidly growing need for remote sensing and Earth observation technology that enables monitoring of world's natural resources and environments, managing exposure to natural and man-made risks and more frequently occurring disasters, and helping the sustainability and productivity of natural and human ecosystems. The improvement in temporal resolution/revisit allows for the large accumulation of images for a specific location, creating a possibility for time series image analysis and eventual real-time assessments of scene dynamics. As an authoritative text, Remote Sensing Time Series Image Processing brings together active and recognized authors in the field of time series image analysis and presents to the readers the current state of knowledge and its future directions.Divided into three parts, the first addresses methods and techniques for generating time series image datasets. In particular, it provides guidance on the selection of cloud and cloud shadow detection algorithms for various applications. Part II examines feature development and information extraction methods for time series imagery. It presents some key remote sensing-based metrics, and their major applications in ecosystems and climate change studies. Part III illustrates various applications of time series image processing in land cover change, disturbance attribution, vegetation dynamics, and urbanization.This book is intended for researchers, practitioners, and students in both remote sensing and imaging science. It can be used as a textbook by undergraduate and graduate students majoring in remote sensing, imaging science, civil and electrical engineering, geography, geosciences, planning, environmental science, land use, energy, and GIS, and as a reference book by practitioners and professionals in the government, commercial, and industrial sectors.

This volume contains the proceedings of the 2017 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'17).

The essential guide to the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Camera Image Quality Benchmarking contains the basic information and approaches for the use of subjectively correlated image quality metrics and outlines a framework for camera benchmarking. The authors show how to quantitatively compare image quality of cameras used for consumer photography. This book helps to fill a void in the literature by detailing the types of objective and subjective metrics that are fundamental to benchmarking still and video imaging devices. Specifically, the book provides an explanation of individual image quality attributes and how they manifest themselves to camera components and explores the key photographic still and video image quality metrics. The text also includes illustrative examples of benchmarking methods so that the practitioner can design a methodology appropriate to the photographic usage in consideration. The authors outline the various techniques used to correlate the measurement results from the objective methods with subjective results. The text also contains a detailed description on how to set up an image quality characterization lab, with examples where the methodological benchmarking approach described has been implemented successfully. This vital resource: Explains in detail the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Provides best practice measurement protocols and methodologies, so readers can develop and define their own camera benchmarking system to industry standards Includes many photographic images and diagrammatical illustrations to clearly convey image quality concepts Champions benchmarking approaches that value the importance of perceptually correlated image quality metrics Written for image scientists, engineers, or managers involved in image quality and evaluating camera performance, Camera Image Quality Benchmarking combines knowledge from many different engineering fields, correlating objective (perception-independent) image quality with subjective (perception-dependent) image quality metrics.

'This book brings together various research methodologies and trends in emerging areas of application of computer vision and image processing for those interested in the research developments of this rapidly growing field'--

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing-one of the first books to integrate these topics together. By improving readers'knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectiv

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.

Ce livre est dédié à l'imagerie de télédétection. Il couvre le cycle global d'utilisation des images de télédétection, depuis leur acquisition par différents capteurs jusqu'à leur exploitation dans diverses applications comme la surveillance des mouvements de la terre, en passant par les traitements qui leur sont appliqués. Il est organisé en trois grandes parties. La première présente les systèmes d'acquisition, les capteurs et les aspects géométriques, ainsi que la physique de la mesure en imagerie optique et en imagerie radar. La deuxième partie est consacrée aux traitements appliqués aux images en distinguant les images optique et multi-spectrales d'une part et les images radar d'autre part. La troisième partie traite des applications de l'imagerie de télédétection : la détection de changements et l'analyse de séries temporelles, la mesure de l'élévation par stéréoscopie ou interférométrie, la mesure de déplacement et l'assimilation de données. Cet ouvrage s'adresse aux étudiants, aux ingénieurs et aux chercheurs concernés par l'observation de la terre et les systèmes d'imagerie, qu'ils soient traiteurs de signaux et d'images, géo-physiciens ou thématiciens.

Image Processing and Acquisition using Python provides readers with a sound foundation in both image acquisition and image processing—one of the first books to integrate these topics together. By improving readers'knowledge of image acquisition techniques and corresponding image processing, the book will help them perform experiments more effectively and cost efficiently as well as analyze and measure more accurately. Long recognized as one of the easiest languages for non-programmers to learn, Python is used in a variety of practical examples.A refresher for more experienced readers, the first part of the book presents an introduction to Python, Python modules, reading and writing images using Python, and an introduction to images. The second part discusses the basics of image processing, including pre/post processing using filters, segmentation, morphological operations, and measurements. The second part describes image acquisition using various modalities, such as x-ray, CT, MRI, light microscopy, and electron microscopy. These modalities encompass most of the common image acquisition methods currently used by researchers in academia and industry. Features Covers both the physical methods of obtaining images and the analytical processing methods required to understand the science behind the images. Contains many examples, detailed derivations, and working Python examples of the techniques. Offers practical tips on image acquisition and processing. Includes numerous exercises to test the reader's skills in Python programming and image processing, with solutions to selected problems, example programs, and images available on the book's web page. New to this edition Machine learning has become an indispensable part of image processing and computer vision, so in this new edition two new chapters are included: one on neural networks and the other on convolutional neural networks. A new chapter on affine transform and many new algorithms. Updated Python code aligned to the latest version of modules.

Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of which are MATLAB based.

Introduction Chapter 1 - Anisotropic Diffusion Chapter 2 - Camera Interface and Canny Edge Detector Chapter 3 - Color Balance and Segmentation (Image Processing) Chapter 4 - Color Quantization and Foveated Imaging Chapter 5 - Digital Image Processing, Drizzle and EasyHDR Pro Chapter 6 - Edge Enhancement and Edge Detection Chapter 7 - Gaussian Blur and GemIdent Chapter 8 - Grassfire Transform and Image Compression

Information on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Wor

Edited and expanded to keep pace with the digital revolution, the new edition of this highly popular and critically acclaimed work provides a comprehensive exploration of imaging science. Brilliantly written and extensively illustrated, The Science of Imaging: An Introduction, Second Edition covers the fundamental laws of physics as well as the cut

As more images and videos are becoming available in compressed formats, researchers have begun designing algorithms for different image operations directly in their domains of representation, leading to faster computation and lower buffer requirements. Image and Video Processing in the Compressed Domain presents the fundamentals, properties, and ap

Illustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI) methods and algorithms for adaptive image processing in regularization, edge detection, and early vision. With three new chapters and updated information throughout, the new edition of this popular reference includes substantial new material that focuses on applications of advanced CI techniques in image processing applications. It introduces new concepts and frameworks that demonstrate how neural networks, support vector machines, fuzzy logic, and evolutionary algorithms can be used to address new challenges in image processing, including low-level image processing, visual content analysis, feature extraction, and pattern recognition.Emphasizing developments in state-of-the-art CI techniques, such as content-based image retrieval, this book continues to provide educators, students, researchers, engineers, and technical managers in visual information processing with the up-to-date understanding required to address contemporary challenges in image content processing and analysis.

This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and compressed sensing. This book weds theory and practice in examining applications in areas such as astronomy, biology, physics, digital media, and forensics. A final chapter explores a paradigm shift in signal processing, showing that previous limits to information sampling and extraction can be overcome in very significant ways. Matlab and IDL code accompany these methods and applications to reproduce the experiments and illustrate the reasoning and methodology of the research are available for download at the associated web site.

Image recognition has become an increasingly dynamic field with new and emerging civil and military applications in security, exploration, and robotics. Written by experts in fractal-based image and video compression, A Concise Introduction to Image Processing using C++ strengthens your knowledge of fundamentals principles in image acquisition, conservation, processing, and manipulation, allowing you to easily apply these techniques in real-world problems. The book presents state-of-the-art image processing methodology, including current industrial practices for image compression, image de-noising methods based on partial differential equations (PDEs), and new image compression methods, such as fractal image compression and wavelet compression. It begins with coverage of representation, and then moves on to communications and processing. It concludes with discussions of processing techniques based on image representations and transformations developed in earlier chapters. The accompanying downloadable resources contain code for all algorithms.Suitable as a text for any course on image processing, the book can also be used as a self-study resource for researchers who need a concise and clear view of current image processing methods and coding examples. The authors introduce mathematical concepts with rigor suitable for readers with some background in calculus, algebra, geometry, and PDEs. All algorithms described are illustrated with code implementation and many images compare the results of different methods. The inclusion of C++ implementation code for each algorithm described enables students and practitioners to build up their own analysis tool.

This book provides the reader with an understanding of what color is, where color comes from, and how color can be used correctly in many different applications. The authors first treat the physics of light and its interaction with matter at the atomic level, so that the origins of color can be appreciated. The intimate relationship between energy

Edited by leaders in the field, with contributions by a panel of experts, Image Processing for Remote Sensing explores new and unconventional mathematics methods. The coverage includes the physics and mathematical algorithms of SAR images, a comprehensive treatment of MRF-based remote sensing image classification, statistical approaches for

Image processing comprises a broad variety of methods that operate on images to produce another image. A unique textbook, Introduction to Image Processing and Analysis establishes the programming involved in image processing and analysis by utilizing skills in C compiler and both Windows and MacOS programming environments. The provided mathematical background illustrates the workings of algorithms and emphasizes the practical reasons for using certain methods, their effects on images, and their appropriate applications. The text concentrates on image processing and measurement and details the implementation of many of the most widely used and most important image processing and analysis algorithms. Homework problems are included in every chapter with solutions available for download from the CRC Press website The chapters work together to combine image processing with image analysis. The book begins with an explanation of familiar pixel array and goes on to describe the use of frequency space. Chapters 1 and 2 deal with the algorithms used in processing steps that are usually accomplished by a combination of measurement and processing operations, as described in chapters 3 and 4. The authors present each concept using a mixture of three mutually supportive tools: a description of the procedure with example images, the relevant mathematical equations behind each concept, and the simple source code (in C), which illustrates basic operations. In particularly, the source code provides a starting point to develop further modifications.Written by John Russ, author of esteemed Image Processing Handbook now in its fifth edition, this book demonstrates functions to improve an image's of features and detail visibility, improve images for printing or transmission, and facilitate subsequent analysis.

Most data from satellites are in image form, thus most books in the remote sensing field deal exclusively with image processing. However, signal processing can contribute significantly in extracting information from the remotely sensed waveforms or time series data. Pioneering the combination of the two processes, Signal and Image Processing for Re

Image processing and a major contribution on microscopy dominate the latest volume of these advances. This volume looks at theory and it's application in a practical sense, with a full account of the methods used and realistic detailed application. The authors do this by examining the latest developments, historic illustrations and mathematical fundamentals of the exciting developments in imaging and applying them to realistic practical situations.Addressing and solving daily issues faced by researchers, consultants and engineers working in this field, makes this book essential reading•Emphasizes broad and in depth article collaborations between world-renowned scientists in the field of image and electron physics•Emphasises theory and it's application in a practical sense•Provides the FIRST full statement of a radical new approach to'phase calibration'and the solution of this important and difficult problem, pioneered by A, Lannes

All of the biomedical measurement technologies, which are now instrumental to the medical field, are essentially useless without proper signal and image processing. Biomedical Signal and Image Processing is unique in providing a comprehensive survey of all the conventional and advanced imaging modalities and the main computational methods used for

Published in cooperation with NATO Public Diplomacy Division.

Software Engineering for Image Processing Systems creates a modern engineering framework for the specification, design, coding, testing, and maintenance of image processing software and systems. The text is designed to benefit not only software engineers, but also workers with backgrounds in mathematics, the physical sciences, and other engineering

The subjects reviewed in the Advances in Imaging and Electron Physics series cover a broad range of themes including microscopy, electromagnetic fields and image coding. This volume concentrates on microscopy and pattern recognition and also electron physics. The text bridges the gap between academic researchers and R&D designers by addressing and solving daily issues, which makes this book essential reading. Emphasizes broad and in depth article collaborations between world-renowned scientists in the field of image and electron physics Presents theory and it's application in a practical sense, providing long awaited solutions and new findings Provides a comprehensive overview of international congress proceedings and associated publications, as source material

Adaptive image processing is one of the most important techniques in visual information processing, especially in early vision such as image restoration, filtering, enhancement, and segmentation. While existing books present some important aspects of the issue, there is not a single book that treats this problem from a viewpoint that is directly li

First published in 1992, The Image Processing Handbook not only set the standard for professional references in this field, but also provided the first text truly accessible to undergraduate students and non-specialists. Each subsequent edition has reflected the continuing rapid advances in image processing, and the fourth edition is no exception.

'Details the latest image processing algorithms and imaging systems for image recognition with diverse applications to the military; the transportation, aerospace, information security, and biomedical industries; radar systems; and image tracking systems.'

Advances in Imaging & Electron Physics merges two long-running serials--Advances in Electronics & Electron Physics and Advances in Optical & Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.

Advances in Imaging & Electron Physics merges two long-running serials--Advances in Electronics & Electron Physics and Advances in Optical & Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.

Space Image Processing covers the design and coding of PC software for processing and manipulating imagery obtained by satellites and other spacecraft. Although the contents relate to several scientific and technological fields, it serves as a programming book, providing readers with essential technical information for developing PC applications. The material focuses on images of the planet and other celestial bodies obtained by orbiting and non-orbiting spacecraft. This book is not about raster graphics in general, but about raster graphics processing as it applies to space imagery. Three parts divide the text: 1. Science - background at an introductory level - scientific principles underlying space imagery and its processing - topics related to space and remote sensing. 2. Technology - topics related to space imagery - geodesy, cartography, image data formats, image processing. 3. Programming - code examples for DOS and Windows programming on the PC - consideration of low-level and C++ code - routines with a tutorial and demonstrative purpose.

Advances in Imaging and Electron Physics merges two long-running serials--Advances in Electronics and Electron Physics and Advances in Optical & Electron Microscopy. It features extended articles onthe physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.

Academic Press is pleased to announce the creation of Advances in Imaging and Electron Physics. This serial publication results from the merger of two long-running serials--Advances in Electronics and Electron Physics and Advances in Optical & Electron Microscopy. Advances in Imaging & Electron Physics will feature extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies,microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains.

Academic Press is pleased to announce the creation of Advances in Imaging and Electron Physics. This serial publication results from the merger of two long running serials--Advances in Electronics and Electron Physics and Advances in Optical & Electron Microscopy. Advances in Imaging & Electron Physics will feature extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies,microlithography, image science and digital image processing, electromagnetic wave propagation, electron microscopy, and the computing methods used in all these domains. Continuation order customers for either of the original Advances will receiveVolume 90, the first combined volume.

Information systems with an abundance of graphics data are growing rapidly due to advances in data storage technology, the development of multimedia communications across networks, and the fact that parallel computers are leading to faster image processing systems. This book addresses image information retrieval and spatial reasoning using an approach called Symbolic Projection, which supports descriptions of the image content on the basis of the spatial relationships between the pictorial objects. Image information systems have a wide variety of applications, including information retrieval on the World Wide Web, medical pictorial archiving, computer-aided design, robotics, and geographical information systems, and this book is comprehensively illustrated with examples from these areas. Symbolic Projection now forms the basis of an enormous number and range of information retrieval algorithms, and also supports query-by-picture and qualitative spatial reasoning. Both authors are international experts in the field, and the book will serve as an excellent source for those working in multimedia systems and image information systems who wish to find out more about this exciting area. An all-inclusive source to the field--all you need to know S-K. Chang is the leading authority in this field, which he pioneered Includes a wide variety of applications, including information retrieval on the World Wide Web, computer-aided design, and geographical information systems

This book is a completely updated, greatly expanded version of the previously successful volume by the author. The Second Edition includes new results and data, and discusses a unified framework and rationale for designing and evaluating image processing algorithms.Written from the viewpoint that image processing supports remote sensing science, this book describes physical models for remote sensing phenomenology and sensors and how they contribute to models for remote-sensing data. The text then presents image processing techniques and interprets them in terms of these models. Spectral, spatial, and geometric models are used to introduce advanced image processing techniques such as hyperspectral image analysis, fusion of multisensor images, and digital elevationmodel extraction from stereo imagery.The material is suited for graduate level engineering, physical and natural science courses, or practicing remote sensing scientists. Each chapter is enhanced by student exercises designed to stimulate an understanding of the material. Over 300 figuresare produced specifically for this book, and numerous tables provide a rich bibliography of the research literature.

Optical Signal Processing is a collection of synopses of the works of many experts in the different fields of optical signal processing. The book also includes systems or algorithms that have been successfully tried and used. The monograph is divided into seven parts. Part I discusses color image processing and white-light Fourier transformations, while Part II covers topics related to pattern recognition such as optical feature extraction and unconventional correlators. Part III deals with temporal signal processing and its related optical architectures, acoustooptic synthetic aperture radar processors, and acoustooptic signal processors. Part IV tackles nonlinear optical processors and waveguide devices. Part V discusses optical and tomographic transformation. Part VI deals with optical numeric processing, optical linear algebra processors, and related algorithm and software. Part VII talks about devices and components and their applications such as fiber-optic delay-line signal processors and spatial light modulators. The text is recommended for engineers and scientists in the field of optical signal processing, especially those who would like to know more of its advancements.