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| digital image processing basics: Fundamentals of Digital Image Processing Anil K. Jain, 1989 |
| digital image processing basics: Principles of Digital Image Processing Wilhelm Burger, Mark J. Burge, 2013-11-18 This textbook is the third of three volumes which provide a modern, algorithmic introduction to digital image processing, designed to be used both by learners desiring a firm foundation on which to build, and practitioners in search of critical analysis and concrete implementations of the most important techniques. This volume builds upon the introductory material presented in the first two volumes with additional key concepts and methods in image processing. Features: practical examples and carefully constructed chapter-ending exercises; real implementations, concise mathematical notation, and precise algorithmic descriptions designed for programmers and practitioners; easily adaptable Java code and completely worked-out examples for easy inclusion in existing applications; uses ImageJ; provides a supplementary website with the complete Java source code, test images, and corrections; additional presentation tools for instructors including a complete set of figures, tables, and mathematical elements. |
| digital image processing basics: Fundamentals of Digital Image Processing Chris Solomon, Toby Breckon, 2011-01-04 This is an introductory to intermediate level text on the science of image processing, which employs the Matlab programming language to illustrate some of the elementary, key concepts in modern image processing and pattern recognition. The approach taken is essentially practical and the book offers a framework within which the concepts can be understood by a series of well chosen examples, exercises and computer experiments, drawing on specific examples from within science, medicine and engineering. Clearly divided into eleven distinct chapters, the book begins with a fast-start introduction to image processing to enhance the accessibility of later topics. Subsequent chapters offer increasingly advanced discussion of topics involving more challenging concepts, with the final chapter looking at the application of automated image classification (with Matlab examples) . Matlab is frequently used in the book as a tool for demonstrations, conducting experiments and for solving problems, as it is both ideally suited to this role and is widely available. Prior experience of Matlab is not required and those without access to Matlab can still benefit from the independent presentation of topics and numerous examples. Features a companion website www.wiley.com/go/solomon/fundamentals containing a Matlab fast-start primer, further exercises, examples, instructor resources and accessibility to all files corresponding to the examples and exercises within the book itself. Includes numerous examples, graded exercises and computer experiments to support both students and instructors alike. |
| digital image processing basics: Digital Image Processing Algorithms and Applications Ioannis Pitas, 2000-02-22 A unique collection of algorithms and lab experiments for practitioners and researchers of digital image processing technology With the field of digital image processing rapidly expanding, there is a growing need for a book that would go beyond theory and techniques to address the underlying algorithms. Digital Image Processing Algorithms and Applications fills the gap in the field, providing scientists and engineers with a complete library of algorithms for digital image processing, coding, and analysis. Digital image transform algorithms, edge detection algorithms, and image segmentation algorithms are carefully gleaned from the literature for compatibility and a track record of acceptance in the scientific community. The author guides readers through all facets of the technology, supplementing the discussion with detailed lab exercises in EIKONA, his own digital image processing software, as well as useful PDF transparencies. He covers in depth filtering and enhancement, transforms, compression, edge detection, region segmentation, and shape analysis, explaining at every step the relevant theory, algorithm structure, and its use for problem solving in various applications. The availability of the lab exercises and the source code (all algorithms are presented in C-code) over the Internet makes the book an invaluable self-study guide. It also lets interested readers develop digital image processing applications on ordinary desktop computers as well as on Unix machines. |
| digital image processing basics: Digital Image Processing for Medical Applications Geoff Dougherty, 2009-04-09 Image processing is a hands-on discipline, and the best way to learn is by doing. This text takes its motivation from medical applications and uses real medical images and situations to illustrate and clarify concepts and to build intuition, insight and understanding. Designed for advanced undergraduates and graduate students who will become end-users of digital image processing, it covers the basics of the major clinical imaging modalities, explaining how the images are produced and acquired. It then presents the standard image processing operations, focusing on practical issues and problem solving. Crucially, the book explains when and why particular operations are done, and practical computer-based activities show how these operations affect real images. All images, links to the public-domain software ImageJ and custom plug-ins, and selected solutions are available from www.cambridge.org/books/dougherty. |
| digital image processing basics: Fundamentals of Digital Image Processing S. Annadurai, 2007 |
| digital image processing basics: Digital Image Processing And Its Basics Vishnu Priya Thotakura, Dr. Asha Latha Bandi, 2022-11-11 This book discusses the use of digital image processing technologies in a wide range of industries. Using machine learning approaches, readers will get an understanding of the many technologies and tactics utilized in the digital image processing and the management of large amounts of data. Students and scholars in topics including engineering, agricultural, and medical image processing would find this book useful in further developing their expertise in these areas. This work is aimed at students with some background in mathematics or computer science, and it uses examples written in the programming language Matlab to introduce and clarify some of the fundamental ideas behind contemporary pattern recognition and image processing techniques. The focus is on application rather than theory, and the book provides a context for understanding the ideas through a sequence of carefully selected examples, activities, and computer experiments that rely on real-world applications in the fields of science, healthcare, and engineering. This book covers important topic like Understanding an image, Resolution and quantization, Bit-plane splicing, Pixels, Image restoration, Blind deconvolution, Shape iv transformation and homogeneous coordinates, Morphological processing, Dilation, erosion and structuring elements within Matlab, The hit-or-miss transformation, Image segmentation and many more. |
| digital image processing basics: Fundamentals of Three-dimensional Digital Image Processing Junichiro Toriwaki, Hiroyuki Yoshida, 2009-05-04 This book is a detailed description of the basics of three-dimensional digital image processing. A 3D digital image (abbreviated as “3D image” below) is a digitalized representation of a 3D object or an entire 3D space, stored in a computer as a 3D array. Whereas normal digital image processing is concerned with screens that are a collection of square shapes called “pixels” and their corresponding density levels, the “image plane” in three dimensions is represented by a division into cubical graphical elements (called “voxels”) that represent corresponding density levels. Inthecontextofimageprocessing,in manycases3Dimageprocessingwill refer to the input of multiple 2D images and performing processing in order to understand the 3D space (or “scene”) that they depict. This is a result of research into how to use input from image sensors such as television cameras as a basis for learning about a 3D scene, thereby replicating the sense of vision for humans or intelligent robots, and this has been the central problem in image processing research since the 1970s. However, a completely di?erent type of image with its own new problems, the 3D digital image discussed in this book, rapidly took prominence in the 1980s, particularly in the ?eld of medical imaging. These were recordings of human bodies obtained through computed (or “computerized”) tomography (CT),imagesthatrecordednotonlytheexternal,visiblesurfaceofthesubject but also, to some degree of resolution, its internal structure. This was a type of image that no one had experienced before. |
| digital image processing basics: Digital Image Processing Gregory A. Baxes, 1994-09-15 Learn about state-of-the-art digital image processing without the complicated math and programming… You don’t have to be a preeminent computer scientist or engineer to get the most out of today’s digital image processing technology. Whether you’re working in medical imaging, machine vision, graphic arts, or just a hobbyist working at home, this book will get you up and running in no time, with all the technical know-how you need to perform sophisticated image processing operations. Designed for end users, as well as an introduction for system designers, developers, and technical managers, this book doesn’t bog you down in complex mathematical formulas or lines of programming code. Instead, in clear down-to-earth language supplemented with numerous example images and the ready-to-run digital image processing program on the enclosed disk, it schools you, step-by-step, in essential digital image processing concepts, principles, techniques, and technologies. Disk contains sample image files and a ready-to-run digital image processing program that lets you do as you learn detailed step-by-step guides to the most commonly used operations, including references to real-world applications and implementations hundreds of before and after images that help illustrate all the operations described comprehensive coverage of current hardware and the best methods for acquiring, displaying, and processing digital images |
| digital image processing basics: Digital Image Processing Wilhelm Burger, Mark J. Burge, 2012-01-19 Written as an introduction for undergraduate students, this textbook covers the most important methods in digital image processing. Formal and mathematical aspects are discussed at a fundamental level and various practical examples and exercises supplement the text. The book uses the image processing environment ImageJ, freely distributed by the National Institute of Health. A comprehensive website supports the book, and contains full source code for all examples in the book, a question and answer forum, slides for instructors, etc. Digital Image Processing in Java is the definitive textbook for computer science students studying image processing and digital processing. |
| digital image processing basics: Fundamentals of Digital Image Processing Dandak Kaniyar, 2025-02-20 Fundamentals of Digital Image Processing is a comprehensive guide that delves into the intricacies of manipulating and analyzing digital images. We provide a thorough exploration of fundamental concepts, techniques, and applications in digital image processing. Catering to both beginners and seasoned professionals, the content spans a wide spectrum. Starting with the basics, we introduce core principles of digital image representation, pixel operations, and color models. We then progress into advanced topics such as image enhancement, filtering, and transformation, offering a deep understanding of the algorithms involved. The book covers image segmentation, a crucial aspect of image analysis, discussing various segmentation techniques and their applications in fields like medical imaging, computer vision, and pattern recognition. We also address the evolving field of image compression, highlighting methods to reduce image size without compromising essential information. One notable strength is our practical approach, integrating theory with hands-on examples and real-world applications. We equip readers with tools to implement image processing algorithms using popular programming languages and software. Case studies illustrate digital image processing's impact in diverse fields, including medicine, remote sensing, and multimedia. Fundamentals of Digital Image Processing is an indispensable resource for academics, researchers, and practitioners, offering theoretical knowledge and practical insights. |
| digital image processing basics: Digital Image Processing Uvais Qidwai, C.H. Chen, 2009-10-15 Avoiding heavy mathematics and lengthy programming details, Digital Image Processing: An Algorithmic Approach with MATLAB® presents an easy methodology for learning the fundamentals of image processing. The book applies the algorithms using MATLAB®, without bogging down students with syntactical and debugging issues. One chapter can typically be completed per week, with each chapter divided into three sections. The first section presents theoretical topics in a very simple and basic style with generic language and mathematics. The second section explains the theoretical concepts using flowcharts to streamline the concepts and to form a foundation for students to code in any programming language. The final section supplies MATLAB codes for reproducing the figures presented in the chapter. Programming-based exercises at the end of each chapter facilitate the learning of underlying concepts through practice. This textbook equips undergraduate students in computer engineering and science with an essential understanding of digital image processing. It will also help them comprehend more advanced topics and sophisticated mathematical material in later courses. A color insert is included in the text while various instructor resources are available on the author’s website. |
| digital image processing basics: Fundamentals of Digital Image Processing Chris Solomon, Toby Breckon, 2011-07-05 This is an introductory to intermediate level text on the science of image processing, which employs the Matlab programming language to illustrate some of the elementary, key concepts in modern image processing and pattern recognition. The approach taken is essentially practical and the book offers a framework within which the concepts can be understood by a series of well chosen examples, exercises and computer experiments, drawing on specific examples from within science, medicine and engineering. Clearly divided into eleven distinct chapters, the book begins with a fast-start introduction to image processing to enhance the accessibility of later topics. Subsequent chapters offer increasingly advanced discussion of topics involving more challenging concepts, with the final chapter looking at the application of automated image classification (with Matlab examples) . Matlab is frequently used in the book as a tool for demonstrations, conducting experiments and for solving problems, as it is both ideally suited to this role and is widely available. Prior experience of Matlab is not required and those without access to Matlab can still benefit from the independent presentation of topics and numerous examples. Features a companion website www.wiley.com/go/solomon/fundamentals containing a Matlab fast-start primer, further exercises, examples, instructor resources and accessibility to all files corresponding to the examples and exercises within the book itself. Includes numerous examples, graded exercises and computer experiments to support both students and instructors alike. |
| digital image processing basics: Digital Image Processing Bernd Jähne, 2005-04-07 This long-established and well-received monograph offers an integral view of image processing - from image acquisition to the extraction of the data of interest – written by a physical scientists for other scientists. Supplements discussion of the general concepts is supplemented with examples from applications on PC-based image processing systems and ready-to-use implementations of important algorithms. Completely revised and extended, the most notable extensions being a detailed discussion on random variables and fields, 3-D imaging techniques and a unified approach to regularized parameter estimation. |
| digital image processing basics: Image Processing Tinku Acharya, Ajoy K. Ray, 2005-10-03 Image processing-from basics to advanced applications Learn how to master image processing and compression with this outstanding state-of-the-art reference. From fundamentals to sophisticated applications, Image Processing: Principles and Applications covers multiple topics and provides a fresh perspective on future directions and innovations in the field, including: * Image transformation techniques, including wavelet transformation and developments * Image enhancement and restoration, including noise modeling and filtering * Segmentation schemes, and classification and recognition of objects * Texture and shape analysis techniques * Fuzzy set theoretical approaches in image processing, neural networks, etc. * Content-based image retrieval and image mining * Biomedical image analysis and interpretation, including biometric algorithms such as face recognition and signature verification * Remotely sensed images and their applications * Principles and applications of dynamic scene analysis and moving object detection and tracking * Fundamentals of image compression, including the JPEG standard and the new JPEG2000 standard Additional features include problems and solutions with each chapter to help you apply the theory and techniques, as well as bibliographies for researching specialized topics. With its extensive use of examples and illustrative figures, this is a superior title for students and practitioners in computer science, wireless and multimedia communications, and engineering. |
| digital image processing basics: Digital Image Processing: Practical Approach Borko Furht, Esad Akar, Whitney Angelica Andrews, 2018 The SpringerBrief covers fundamentals of digital image processing including image concept, image file formats, creating user interfaces and many practical examples of processing images using C++ and Java. These practical examples include among other creating image histograms, performing lossless image compression, detecting change in colors, similarity-based image retrieval and others. All practical examples are accompanied with an explanation how to create programs and the obtained results. This SpringerBrief can be very useful for the undergraduate courses on image processing, providing students with the basic tools in image analysis and processing. Practitioners and researchers working in this field will also find this research useful. |
| digital image processing basics: Digital Image Processing and Analysis Scott E Umbaugh, 2022-12-30 Digital Image Enhancement, Restoration and Compression focuses on human vision-based imaging application development. Examples include making poor images look better, the development of advanced compression algorithms, special effects imaging for motion pictures and the restoration of satellite images distorted by atmospheric disturbance. This book presents a unique engineering approach to the practice of digital imaging, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored. The book includes chapters on imaging systems and software, the human visual system, image transforms, image filtering, image enhancement, image restoration, and image compression. Numerous examples, including over 700 color images, are used to illustrate the concepts discussed. Readers can explore their own application development with any programming language, including C/C++, MATLAB®, Python and R, and software is provided for both the Windows/C/C++ and MATLAB environments. The book can be used by the academic community in teaching and research, with over 1,000 PowerPoint slides and a complete solutions manual to the over 230 included problems. It can also be used for self-study by those involved with application development, whether they are engineers, scientists or artists. The new edition has been extensively updated and includes numerous problems and programming exercises that will help the reader and student develop their skills. |
| digital image processing basics: Digital Image Processing,2/e Gonzalez, 2002 |
| digital image processing basics: Computer Imaging Scott E Umbaugh, 2005-01-27 Computer Imaging: Digital Image Analysis and Processing brings together analysis and processing in a unified framework, providing a valuable foundation for understanding both computer vision and image processing applications. Taking an engineering approach, the text integrates theory with a conceptual and application-oriented style, allowing you to immediately understand how each topic fits into the overall structure of practical application development. Divided into five major parts, the book begins by introducing the concepts and definitions necessary to understand computer imaging. The second part describes image analysis and provides the tools, concepts, and models required to analyze digital images and develop computer vision applications. Part III discusses application areas for the processing of images, emphasizing human visual perception. Part IV delivers the information required to apply a CVIPtools environment to algorithm development. The text concludes with appendices that provide supplemental imaging information and assist with the programming exercises found in each chapter. The author presents topics as needed for understanding each practical imaging model being studied. This motivates the reader to master the topics and also makes the book useful as a reference. The CVIPtools software integrated throughout the book, now in a new Windows version, provides practical examples and encourages you to conduct additional exploration via tutorials and programming exercises provided with each chapter. |
| digital image processing basics: Digital Image Processing Rafael C. Gonzalez, Richard E. Woods, 2018 |
| digital image processing basics: Digital Image Fundamentals and Image Transforms Mr. Rohit Manglik, 2024-04-06 EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels. |
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Digital Image Processing Mock Tests Chapter 1-10 eBook covers problem solving exam tests from computer science textbook and practical eBook chapter wise as: Chapter 1: Color Image Processing MCQ Chapter 2: Digital Image Fundamentals MCQ Chapter 3: Filtering in Frequency Domain MCQ Chapter 4: Image Compression MCQ Chapter 5: Image Restoration and Reconstruction MCQ Chapter 6: Image Segmentation MCQ Chapter 7: Intensity Transformation and Spatial Filtering MCQ Chapter 8: Introduction to Digital Image Processing MCQ Chapter 9: Morphological Image Processing MCQ Chapter 10: Wavelet and Multiresolution Processing MCQ The Color Image Processing MCQ PDF e-Book: Chapter 1 practice test to solve MCQ questions on Basics of full color image processing, color fundamentals in color image processing, color models, color transformation, pseudo color image processing, smoothing, and sharpening. The Digital Image Fundamentals MCQ PDF e-Book: Chapter 2 practice test to solve MCQ questions on Representing digital image, elements of visual perception, image interpolation, image sampling and quantization, image sensing and acquisition, light and electromagnetic spectrum, simple image formation model, spatial and intensity resolution. The Filtering in Frequency Domain MCQ PDF e-Book: Chapter 3 practice test to solve MCQ questions on Basics of filtering in frequency domain, filtering concepts, 10d discrete Fourier transform, background of intensity transformation, convolution, discrete Fourier transform of one variable, extension to functions of two variables, image interpolation and resampling, preliminary concepts, properties of 10d DFT, sampling, and Fourier transform of sampled function. The Image Compression MCQ PDF e-Book: Chapter 4 practice test to solve MCQ questions on Fundamentals of image compression, image compression models, image compression techniques, coding redundancy, fidelity criteria, image compressors, and measuring image information. The Image Restoration and Reconstruction MCQ PDF e-Book: Chapter 5 practice test to solve MCQ questions on Model of image restoration process, image reconstruction from projections, constrained least squares filtering, convolution, estimating degradation function, geometric mean filter, image processing algorithms, inverse filtering, linear position invariant degradations, minimum mean square error filtering, noise models, periodic noise reduction using frequency domain filtering, and restoration in presence of noise. The Image Segmentation MCQ PDF e-Book: Chapter 6 practice test to solve MCQ questions on Fundamentals of image segmentation, image processing algorithms, edge models in image segmentation, edge detection in image processing, edge detection in segmentation, edge models, line detection in digital image processing, line detection in image segmentation, point line and edge detection, and preview in image segmentation. The Intensity Transformation and Spatial Filtering MCQ PDF e-Book: Chapter 7 practice test to solve MCQ questions on Background of intensity transformation, fundamentals of spatial filtering, basic intensity transformations functions, bit plane slicing, contrast stretching, examples in intensity transformation, histogram equalization, histogram matching, histogram processing, image negatives, intensity level slicing, local histogram processing, log transformation, piecewise linear transformation functions, power law transformation, smoothing spatial filters, spatial correlation, and convolution. The Introduction to Digital Image Processing MCQ PDF e-Book: Chapter 8 practice test to solve MCQ questions on Origin of digital image processing, fundamental steps in digital image processing, example of using image processing, examples of using modalities, gamma rays imaging, imaging in a radio wave, imaging in microwave band, imaging in ultraviolet band, imaging in visible and infrared band, and x-ray imaging. The Morphological Image Processing MCQ PDF e-Book: Chapter 9 practice test to solve MCQ questions on Morphological image processing basics, preliminaries in morphological image processing, erosion and dilation, hit or miss transformation, image erosion, morphological analysis, and morphological opening closing. The Wavelet and Multiresolution Processing MCQ PDF e-Book: Chapter 10 practice test to solve MCQ questions on Introduction to wavelet and multiresolution processing, multiresolution expansions, and wavelet transforms in one dimension. |
| digital image processing basics: Digital Image Processing Rafael C. Gonzalez, Richard Eugene Woods, 2008 A comprehensive digital image processing book that reflects new trends in this field such as document image compression and data compression standards. The book includes a complete rewrite of image data compression, a new chapter on image analysis, and a new section on image morphology. |
| digital image processing basics: Fundamentals of Digital Image Processing in Medical Applications Dr. Amruth Ramesh Thelkar, 2025-01-06 The book “Fundamentals of Digital Image Processing in Medical Applications” delves into the complex relationship between technology and healthcare, emphasizing the significant impact of image processing on diagnostics and treatment. This book encompasses a broad spectrum of subjects, commencing with the fundamental principles of digital image processing and progressing to intricate techniques that are crucial to contemporary medical imaging systems. It explores the techniques that are employed in medical applications to improve image quality, including contrast adjustment, noise reduction, and edge detection, to give readers a comprehensive comprehension of their application. Pattern recognition, automated diagnostics, and image classification are all examples of artificial intelligence that are revolutionizing healthcare practices. A particular emphasis is placed on their integration into the field. The book also tackles the critical challenges in medical imaging, including the necessity for precise tumor detection, multimodal image integration, and the storage and retrieval of medical images. “Fundamentals of Digital Image Processing in Medical Applications” is a valuable educational resource and reference for anyone interested in understanding the intersection of image processing and medical technology, as it provides a diverse array of theoretical foundations, real-world applications, and emerging trends. |
| digital image processing basics: Digital Image Processing Mr. Rohit Manglik, 2024-07-22 EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels. |
| digital image processing basics: Digital Image Processing Nick Efford, 2000 CD-ROM contains Java classes for use in developing image processing software as well as completed image processing software. |
| digital image processing basics: Practical Image and Video Processing Using MATLAB Oge Marques, 2011-08-04 UP-TO-DATE, TECHNICALLY ACCURATE COVERAGE OF ESSENTIAL TOPICS IN IMAGE AND VIDEO PROCESSING This is the first book to combine image and video processing with a practical MATLAB®-oriented approach in order to demonstrate the most important image and video techniques and algorithms. Utilizing minimal math, the contents are presented in a clear, objective manner, emphasizing and encouraging experimentation. The book has been organized into two parts. Part I: Image Processing begins with an overview of the field, then introduces the fundamental concepts, notation, and terminology associated with image representation and basic image processing operations. Next, it discusses MATLAB® and its Image Processing Toolbox with the start of a series of chapters with hands-on activities and step-by-step tutorials. These chapters cover image acquisition and digitization; arithmetic, logic, and geometric operations; point-based, histogram-based, and neighborhood-based image enhancement techniques; the Fourier Transform and relevant frequency-domain image filtering techniques; image restoration; mathematical morphology; edge detection techniques; image segmentation; image compression and coding; and feature extraction and representation. Part II: Video Processing presents the main concepts and terminology associated with analog video signals and systems, as well as digital video formats and standards. It then describes the technically involved problem of standards conversion, discusses motion estimation and compensation techniques, shows how video sequences can be filtered, and concludes with an example of a solution to object detection and tracking in video sequences using MATLAB®. Extra features of this book include: More than 30 MATLAB® tutorials, which consist of step-by-step guides toexploring image and video processing techniques using MATLAB® Chapters supported by figures, examples, illustrative problems, and exercises Useful websites and an extensive list of bibliographical references This accessible text is ideal for upper-level undergraduate and graduate students in digital image and video processing courses, as well as for engineers, researchers, software developers, practitioners, and anyone who wishes to learn about these increasingly popular topics on their own. |
| digital image processing basics: Digital Signal Processing Techniques and Applications in Radar Image Processing Bu-Chin Wang, 2008-08-29 A self-contained approach to DSP techniques and applications in radar imaging The processing of radar images, in general, consists of three major fields: Digital Signal Processing (DSP); antenna and radar operation; and algorithms used to process the radar images. This book brings together material from these different areas to allow readers to gain a thorough understanding of how radar images are processed. The book is divided into three main parts and covers: * DSP principles and signal characteristics in both analog and digital domains, advanced signal sampling, and interpolation techniques * Antenna theory (Maxwell equation, radiation field from dipole, and linear phased array), radar fundamentals, radar modulation, and target-detection techniques (continuous wave, pulsed Linear Frequency Modulation, and stepped Frequency Modulation) * Properties of radar images, algorithms used for radar image processing, simulation examples, and results of satellite image files processed by Range-Doppler and Stolt interpolation algorithms The book fully utilizes the computing and graphical capability of MATLAB? to display the signals at various processing stages in 3D and/or cross-sectional views. Additionally, the text is complemented with flowcharts and system block diagrams to aid in readers' comprehension. Digital Signal Processing Techniques and Applications in Radar Image Processing serves as an ideal textbook for graduate students and practicing engineers who wish to gain firsthand experience in applying DSP principles and technologies to radar imaging. |
| digital image processing basics: Fundamentals of Three-dimensional Digital Image Processing Junichiro Toriwaki, Hiroyuki Yoshida, 2009-04-23 This book is a detailed description of the basics of three-dimensional digital image processing. A 3D digital image (abbreviated as “3D image” below) is a digitalized representation of a 3D object or an entire 3D space, stored in a computer as a 3D array. Whereas normal digital image processing is concerned with screens that are a collection of square shapes called “pixels” and their corresponding density levels, the “image plane” in three dimensions is represented by a division into cubical graphical elements (called “voxels”) that represent corresponding density levels. Inthecontextofimageprocessing,in manycases3Dimageprocessingwill refer to the input of multiple 2D images and performing processing in order to understand the 3D space (or “scene”) that they depict. This is a result of research into how to use input from image sensors such as television cameras as a basis for learning about a 3D scene, thereby replicating the sense of vision for humans or intelligent robots, and this has been the central problem in image processing research since the 1970s. However, a completely di?erent type of image with its own new problems, the 3D digital image discussed in this book, rapidly took prominence in the 1980s, particularly in the ?eld of medical imaging. These were recordings of human bodies obtained through computed (or “computerized”) tomography (CT),imagesthatrecordednotonlytheexternal,visiblesurfaceofthesubject but also, to some degree of resolution, its internal structure. This was a type of image that no one had experienced before. |
| digital image processing basics: Digital Image Processing with Application to Digital Cinema K. Thyagarajan, 2006 First Published in 2006. Routledge is an imprint of Taylor & Francis, an informa company. |
| digital image processing basics: Digital Image Analysis of Microbes M. H. F. Wilkinson, F. Schut, 1998-06-08 Die Entwicklung digitaler Bildverarbeitung, gekoppelt an Mikroskopsysteme, ermöglichte in neuerer Zeit einen zunehmenden Einsatz der Bildanalyse von Mikroben - ein wertvolles Hilfsmittel für das Verständnis der Strukturen, des Verhaltens und der Diversität mikrobieller Populationen. Dieser aktuelle, interdisziplinär angelegte Abriß der digitalen Bildverarbeitung wurde von einem internationalen Team von Mikrobiologen, Biotechnologen und Computerwissenschaftlern verfaßt. (04/98) |
| digital image processing basics: Encyclopedia of Image Processing Phillip A. Laplante, 2018-11-08 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. |
| digital image processing basics: Image Sensors and Signal Processing for Digital Still Cameras Junichi Nakamura, 2017-12-19 Shrinking pixel sizes along with improvements in image sensors, optics, and electronics have elevated DSCs to levels of performance that match, and have the potential to surpass, that of silver-halide film cameras. Image Sensors and Signal Processing for Digital Still Cameras captures the current state of DSC image acquisition and signal processing technology and takes an all-inclusive look at the field, from the history of DSCs to future possibilities. The first chapter outlines the evolution of DSCs, their basic structure, and their major application classes. The next few chapters discuss high-quality optics that meet the requirements of better image sensors, the basic functions and performance parameters of image sensors, and detailed discussions of both CCD and CMOS image sensors. The book then discusses how color theory affects the uses of DSCs, presents basic image processing and camera control algorithms and examples of advanced image processing algorithms, explores the architecture and required performance of signal processing engines, and explains how to evaluate image quality for each component described. The book closes with a look at future technologies and the challenges that must be overcome to realize them. With contributions from many active DSC experts, Image Sensors and Image Processing for Digital Still Cameras offers unparalleled real-world coverage and opens wide the door for future innovation. |
| digital image processing basics: Introduction to Digital Image Processing with MATLAB Alasdair McAndrew, Jung Hua Wang, Chun Shun Tseng, 2010 |
| digital image processing basics: Handbook of Image and Video Processing Alan C. Bovik, 2010-07-21 55% new material in the latest edition of this must-have for students and practitioners of image & video processing!This Handbook is intended to serve as the basic reference point on image and video processing, in the field, in the research laboratory, and in the classroom. Each chapter has been written by carefully selected, distinguished experts specializing in that topic and carefully reviewed by the Editor, Al Bovik, ensuring that the greatest depth of understanding be communicated to the reader. Coverage includes introductory, intermediate and advanced topics and as such, this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers and students with a highly accessible resource for learning and using image/video processing theory and algorithms • Includes a new chapter on image processing education, which should prove invaluable for those developing or modifying their curricula • Covers the various image and video processing standards that exist and are emerging, driving today's explosive industry • Offers an understanding of what images are, how they are modeled, and gives an introduction to how they are perceived • Introduces the necessary, practical background to allow engineering students to acquire and process their own digital image or video data • Culminates with a diverse set of applications chapters, covered in sufficient depth to serve as extensible models to the reader's own potential applications About the Editor... Al Bovik is the Cullen Trust for Higher Education Endowed Professor at The University of Texas at Austin, where he is the Director of the Laboratory for Image and Video Engineering (LIVE). He has published over 400 technical articles in the general area of image and video processing and holds two U.S. patents. Dr. Bovik was Distinguished Lecturer of the IEEE Signal Processing Society (2000), received the IEEE Signal Processing Society Meritorious Service Award (1998), the IEEE Third Millennium Medal (2000), and twice was a two-time Honorable Mention winner of the international Pattern Recognition Society Award. He is a Fellow of the IEEE, was Editor-in-Chief, of the IEEE Transactions on Image Processing (1996-2002), has served on and continues to serve on many other professional boards and panels, and was the Founding General Chairman of the IEEE International Conference on Image Processing which was held in Austin, Texas in 1994.* No other resource for image and video processing contains the same breadth of up-to-date coverage* Each chapter written by one or several of the top experts working in that area* Includes all essential mathematics, techniques, and algorithms for every type of image and video processing used by electrical engineers, computer scientists, internet developers, bioengineers, and scientists in various, image-intensive disciplines |
| digital image processing basics: Handbook of Image and Video Processing Alan Conrad Bovik, 2000 The Handbook of Image and Video Processing contains a comprehensive and highly accessible presentation of all essential mathematics, techniques, and algorithms for every type of image and video processing used by scientists and engineers. The timely volume will provide both the novice and the seasoned practitioner with the necessary information and skills to be able to develop algorithms and applications for multimedia, digital imaging, digital video, telecommunications, and World Wide Web industries. Handbook of Image and Video Processing will also serve as a textbook for courses such as digital image processing, digital image analysis, digital video, video communications, multimedia, and biomedical image processing in the departments of electrical and computer engineering and computer science. * No other resource contains the same breadth of up-to-date coverage * Contains over 100 example algorithm illustrations * Contains a series of extremely accessible tutorial chapters * Indispensible for researchers in telecommunications, internet applications, multimedia, and nearly every branch of science |
| digital image processing basics: Digital Image Processing and Analysis CHANDA, BHABATOSH, MAJUMDER, DWIJESH DUTTA, 2011-10-30 The second edition of this extensively revised and updated text is a result of the positive feedback and constructive suggestions received from academics and students alike. It discusses the fundamentals as well as the advances in digital image processing and analysis—both theory and practice—to fulfil the needs of students pursuing courses in Computer Science and Engineering (CSE) and Electronics and Communication Engineering (ECE), both at undergraduate and postgraduate levels. It is also considered useful for teachers, professional engineers and researchers. The second edition has three objectives. First, each and every chapter has been modified in the light of recent advances as well as emerging concepts. Second, a good deal of colour image processing has been incorporated. A large number of line drawings and images have been included to make the book student friendly. Third, some new problems have been added in almost all chapters to test the student’s understanding of the real-life problems. The other distinguishing features of the book are : A summary at the end of the chapter to help the student capture the key points. About 320 line drawings and 280 photographs for easy assimilation of the concepts. Chapter-end problems for extensive practice and research. |
| digital image processing basics: Digital Image Processing S. Jayaraman, S. Esakkirajan, T. Veerakumar, 2009 Meant for students and practicing engineers, this book provides a clear, comprehensive and up-to-date introduction to Digital Image Processing in a pragmatic style. An illustrative approach, practical examples and MATLAB applications given in the book help in bringing the theory to life. |
| digital image processing basics: Digital Image Processing Using Python Dr. Manish Kashyap, 2025-01-28 DESCRIPTION “Digital Image Processing Using Python offers a comprehensive guide to mastering image processing techniques through practical Python implementations. It equips you with the essential tools and knowledge to manipulate, analyze, and transform digital images using the powerful programming language, Python. This book offers a comprehensive exploration of digital image processing, combining theoretical foundations with practical applications. Starting with fundamental concepts like image representation and pixel neighborhoods, the book teaches Python programming and essential libraries for image manipulation. It covers a wide range of techniques, including spatial and frequency domain filtering, non-linear processing, noise reduction, wavelet transforms, and binary morphology. Advanced topics such as phase-based processing, multi-resolution analysis, and morphological operations are also explored in depth. The book provides practical examples and exercises to reinforce learning and equip readers with the skills needed to effectively process and analyze digital images for various applications. By integrating Python code with visual examples, you will gain practical experience and insights that are directly applicable to your work. This approach ensures that you not only learn theoretical concepts but also understand how to implement them effectively in real-world situations. KEY FEATURES ● Builds a strong foundation in digital image processing, covering essential topics from basics to advanced techniques. ● Includes practical exercises to master Python programming and essential libraries like OpenCV and NumPy for image manipulation tasks. ● Applies concepts to real-world scenarios like image restoration, object detection, and medical imaging. WHAT YOU WILL LEARN ● Implement image processing techniques using Python libraries and tools. ● Understand core concepts like filtering, segmentation, and enhancement. ● Apply practical Python code to real-world image processing tasks. ● Develop skills to analyze and manipulate digital images effectively. ● Create and visualize image processing algorithms with hands-on examples. WHO THIS BOOK IS FOR This book is perfect for undergraduate and master's level students seeking to grasp image processing concepts or professionals working in fields like computer vision, artificial intelligence, or medical imaging. TABLE OF CONTENTS 1. Introduction to Digital Images 2. Python Fundamentals and Related Libraries 3. Playing with Digital Images 4. Spatial Domain Processing 5. Frequency Domain Image Processing 6. Non-linear Image Processing and the Issue of Phase 7. Noise and Image Restoration 8. Wavelet Transform and Multi-resolution Analysis 9. Binary Morphology |
| digital image processing basics: Applied Medical Image Processing Wolfgang Birkfellner, 2016-04-19 A widely used, classroom-tested text, Applied Medical Image Processing: A Basic Course delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field. Avoiding excessive mathematical formalisms, the book presents key principles by implementing algorithms from scratch and usin |
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