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This book contains a compilation of a number of blogs from the MicroZed Chronicles which examines how to develop image processing systems using Xilinx FPGA and heterogeneous SoC. The initial chapters are new and explain the principles behind image processing sensors and sensor selection parameters.

Just imagine the possibilities with the iGen 20/20 2.6x Day & Night Vision Monocular, a high-tech device that brings the future of night vision to your fingertips. This advanced monocular is powered by proprietary iGEN technology, offering adjustable light amplification ranging from 300x to a staggering 10,000x. This feature ensures optimal visibility in varying light conditions, from twilight to pitch black darkness.Experience a smooth viewing experience with the variable frame rate feature, which can be adjusted from 2 fps to 30 fps, surpassing the performance of Gen 2 night vision devices and comparable to Gen 3 models. This powerful monocular is equipped with Infrared Intelligence that offers three distinct modes, adjusting the wattage automatically as needed to cater to different levels of darkness.The iGen 20/20 2.6x Monocular boasts enhanced infrared sensitivity, offering double the sensitivity of traditional intensifier tube technology. This feature ensures clear, detailed images even in low-light conditions, making it an ideal tool for outdoor enthusiasts engaged in activities like hunting, camping, hiking, and birdwatching.For those who wish to capture their observations, this versatile device features a video composite output for direct recording to an external device. Simply connect a composite video cable (RCA cable, not included) and select between NTSC or PAL formats. This feature allows you to document and share your experiences in the great outdoors. In conclusion, the iGen 20/20 2.6x Day & Night Vision Monocular with Image Processing is a durable, powerful, and versatile tool that enhances your outdoor adventures, day or night.

This book contains a compilation of a number of blogs from the MicroZed Chronicles which examines how to develop image processing systems using Xilinx FPGA and heterogeneous SoC. The initial chapters are new and explain the principles behind image processing sensors and sensor selection parameters.

This book is a companion book to the comprehensive text entitled Image Processing, Analysis, and Machine Vision by M. Sonka, V. Hlavac, and R. Boyle. This workbook provides additional material for readers of Sonka and is similarly structured. Written for students, teachers and practitioners to acquire practical understanding in a hands on fashion, this book provides the reader with short-answer questions, problems and selected algorithms from the main text using MATLAB in levels of varying difficulty. These resources can be used as extra practice for students to reinforce the material studied within the main text or can be useful as test materials for teachers. A solutions manual is available for Instructors for the problems within this workbook.

Image Processing for Cinema presents a detailed overview of image processing techniques that are used in practice in digital cinema. The book shows how image processing has become ubiquitous in movie-making, from shooting to exhibition. It covers all the ways in which image processing algorithms are used to enhance, restore, adapt, and convert moving images. These techniques and algorithms make the images look as good as possible while exploiting the capabilities of cameras, projectors, and displays.The author focuses on the ideas behind the methods, rather than proofs and derivations. The first part of the text presents fundamentals on optics and color. The second part explains how cameras work and details all the image processing algorithms that are applied in-camera. With an emphasis on state-of-the-art methods that are actually used in practice, the last part describes image processing algorithms that are applied offline to solve a variety of problems.The book is designed for advanced undergraduate and graduate students in applied mathematics, image processing, computer science, and related fields. It is also suitable for academic researchers and professionals in the movie industry.

From the reviews of the First Edition:

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

Image Processing for Cinema presents a detailed overview of image processing techniques that are used in practice in digital cinema. The book shows how image processing has become ubiquitous in movie-making, from shooting to exhibition. It covers all the ways in which image processing algorithms are used to enhance, restore, adapt, and convert moving images. These techniques and algorithms make the images look as good as possible while exploiting the capabilities of cameras, projectors, and displays.The author focuses on the ideas behind the methods, rather than proofs and derivations. The first part of the text presents fundamentals on optics and color. The second part explains how cameras work and details all the image processing algorithms that are applied in-camera. With an emphasis on state-of-the-art methods that are actually used in practice, the last part describes image processing algorithms that are applied offline to solve a variety of problems.The book is designed for advanced undergraduate and graduate students in applied mathematics, image processing, computer science, and related fields. It is also suitable for academic researchers and professionals in the movie industry.

Now in its fifth edition, John C. Russ’s monumental image processing reference is an even more complete, modern, and hands-on tool than ever before. The Image Processing Handbook, Fifth Edition is fully updated and expanded to reflect the latest developments in the field. Written by an expert with unequalled experience and authority, it offers clear guidance on how to create, select, and use the most appropriate algorithms for a specific application. What’s new in the Fifth Edition? ·       A new chapter on the human visual process that explains which visual cues elicit a response from the viewer ·       Description of the latest hardware and software for image acquisition and printing, reflecting the proliferation of the digital camera ·       New material on multichannel images, including a major section on principal components analysis ·       Expanded sections on deconvolution, extended dynamic range images, and image enlargement and interpolation ·       More than 600 new and revised figures and illustrations for a total of more than 2000 illustrations ·       20% more references to the most up-to-date literature Written in a relaxed and reader-friendly style, The Image Processing Handbook, Fifth Edition guides you through the myriad tools available for image processing and helps you understand how to select and apply each one.

Now in its fifth edition, John C. Russ’s monumental image processing reference is an even more complete, modern, and hands-on tool than ever before. The Image Processing Handbook, Fifth Edition is fully updated and expanded to reflect the latest developments in the field. Written by an expert with unequalled experience and authority, it offers clear guidance on how to create, select, and use the most appropriate algorithms for a specific application. What’s new in the Fifth Edition? ·       A new chapter on the human visual process that explains which visual cues elicit a response from the viewer ·       Description of the latest hardware and software for image acquisition and printing, reflecting the proliferation of the digital camera ·       New material on multichannel images, including a major section on principal components analysis ·       Expanded sections on deconvolution, extended dynamic range images, and image enlargement and interpolation ·       More than 600 new and revised figures and illustrations for a total of more than 2000 illustrations ·       20% more references to the most up-to-date literature Written in a relaxed and reader-friendly style, The Image Processing Handbook, Fifth Edition guides you through the myriad tools available for image processing and helps you understand how to select and apply each one.

With contributions by numerous experts

Unread book in perfect condition.

Following the success of the first edition, this thoroughly updated second edition of Image Processing: The Fundamentals will ensure that it remains the ideal text for anyone seeking an introduction to the essential concepts of image processing. New material includes image processing and colour, sine and cosine transforms, Independent Component Analysis (ICA), phase congruency and the monogenic signal and several other new topics. These updates are combined with coverage of classic topics in image processing, such as orthogonal transforms and image enhancement, making this a truly comprehensive text on the subject. Key features: Presents material at two levels of difficulty: the main text addresses the fundamental concepts and presents a broad view of image processing, whilst more advanced material is interleaved in boxes throughout the text, providing further reference for those who wish to examine each technique in depth. Contains a large number of fully worked out examples. Focuses on an understanding of how image processing methods work in practice. Illustrates complex algorithms on a step-by-step basis, and lists not only the good practices but also identifies the pitfalls in each case. Uses a clear question and answer structure. Includes a CD containing the MATLAB® code of the various examples and algorithms presented in the book. There is also an accompanying website with slides available for download for instructors as a teaching resource. Image Processing: The Fundamentals, Second Edition is an ideal teaching resource for both undergraduate and postgraduate students. It will also be of value to researchers of various disciplines from medicine to mathematics with a professional interest in image processing

Following the success of the first edition, this thoroughly updated second edition of Image Processing: The Fundamentals will ensure that it remains the ideal text for anyone seeking an introduction to the essential concepts of image processing. New material includes image processing and colour, sine and cosine transforms, Independent Component Analysis (ICA), phase congruency and the monogenic signal and several other new topics. These updates are combined with coverage of classic topics in image processing, such as orthogonal transforms and image enhancement, making this a truly comprehensive text on the subject. Key features: Presents material at two levels of difficulty: the main text addresses the fundamental concepts and presents a broad view of image processing, whilst more advanced material is interleaved in boxes throughout the text, providing further reference for those who wish to examine each technique in depth. Contains a large number of fully worked out examples. Focuses on an understanding of how image processing methods work in practice. Illustrates complex algorithms on a step-by-step basis, and lists not only the good practices but also identifies the pitfalls in each case. Uses a clear question and answer structure. Includes a CD containing the MATLAB® code of the various examples and algorithms presented in the book. There is also an accompanying website with slides available for download for instructors as a teaching resource. Image Processing: The Fundamentals, Second Edition is an ideal teaching resource for both undergraduate and postgraduate students. It will also be of value to researchers of various disciplines from medicine to mathematics with a professional interest in image processing

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

This is the first book that provides a balanced treatment of image processing basics and software principles used in the practical application of image processing. Working in the MATLAB computing environment, it provides a stable, well-supported set of software tools capable of addressing a broad spectrum of applications in digital image processing. The major areas covered include intensity transformations, linear and nonlinear spatial filtering, filtering in the frequency domain, image restoration and registration, color image processing, wavelets, image data compression, morpohological image processing, image segmentation, regions and boundary representation and description, and object recognition. For software developers working with image processing.

Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.

This revised and expanded new edition of an internationally successful classic presents an accessible introduction to the key methods in digital image processing for both practitioners and teachers. Emphasis is placed on practical application, presenting precise algorithmic descriptions in an unusually high level of detail, while highlighting direct connections between the mathematical foundations and concrete implementation. The text is supported by practical examples and carefully constructed chapter-ending exercises drawn from the authors' years of teaching experience, including easily adaptable Java code and completely worked out examples. Source code, test images and additional instructor materials are also provided at an associated website. Digital Image Processing is the definitive textbook for students, researchers, and professionals in search of critical analysis and modern implementations of the most important algorithms in the field, and is also eminently suitable for self-study.

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A cookbook of algorithms for common image processing applications Thanks to advances in computer hardware and software, algorithms have been developed that support sophisticated image processing without requiring an extensive background in mathematics. This bestselling book has been fully updated with the newest of these, including 2D vision methods in content-based searches and the use of graphics cards as image processing computational aids. It’s an ideal reference for software engineers and developers, advanced programmers, graphics programmers, scientists, and other specialists who require highly specialized image processing. Algorithms now exist for a wide variety of sophisticated image processing applications required by software engineers and developers, advanced programmers, graphics programmers, scientists, and related specialists This bestselling book has been completely updated to include the latest algorithms, including 2D vision methods in content-based searches, details on modern classifier methods, and graphics cards used as image processing computational aids Saves hours of mathematical calculating by using distributed processing and GPU programming, and gives non-mathematicians the shortcuts needed to program relatively sophisticated applications. Algorithms for Image Processing and Computer Vision, 2nd Edition provides the tools to speed development of image processing applications.