Partial Differential Equation Methods for Image Inpainting PDF Download
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Author: Carola-Bibiane Schönlieb
Publisher: Cambridge University Press
ISBN: 1107001005
Category : Computers
Languages : en
Pages : 265
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Book Description
This book introduces the mathematical concept of partial differential equations (PDE) for virtual image restoration. It provides insight in mathematical modelling, partial differential equations, functional analysis, variational calculus, optimisation and numerical analysis. It is addressed towards generally informed mathematicians and graduate students in mathematics with an interest in image processing and mathematical analysis.
Author: Carola-Bibiane Schönlieb
Publisher: Cambridge University Press
ISBN: 1107001005
Category : Computers
Languages : en
Pages : 265
Get Book Here
Book Description
This book introduces the mathematical concept of partial differential equations (PDE) for virtual image restoration. It provides insight in mathematical modelling, partial differential equations, functional analysis, variational calculus, optimisation and numerical analysis. It is addressed towards generally informed mathematicians and graduate students in mathematics with an interest in image processing and mathematical analysis.
Author: Carola-Bibiane Schönlieb
Publisher: Cambridge University Press
ISBN: 1316404587
Category : Mathematics
Languages : en
Pages : 265
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Book Description
This book is concerned with digital image processing techniques that use partial differential equations (PDEs) for the task of image 'inpainting', an artistic term for virtual image restoration or interpolation, whereby missing or occluded parts in images are completed based on information provided by intact parts. Computer graphic designers, artists and photographers have long used manual inpainting to restore damaged paintings or manipulate photographs. Today, mathematicians apply powerful methods based on PDEs to automate this task. This book introduces the mathematical concept of PDEs for virtual image restoration. It gives the full picture, from the first modelling steps originating in Gestalt theory and arts restoration to the analysis of resulting PDE models, numerical realisation and real-world application. This broad approach also gives insight into functional analysis, variational calculus, optimisation and numerical analysis and will appeal to researchers and graduate students in mathematics with an interest in image processing and mathematical analysis.
Author: Xue-Cheng Tai
Publisher: Springer Science & Business Media
ISBN: 3540332677
Category : Computers
Languages : en
Pages : 440
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Book Description
This book publishes a collection of original scientific research articles that address the state-of-art in using partial differential equations for image and signal processing. Coverage includes: level set methods for image segmentation and construction, denoising techniques, digital image inpainting, image dejittering, image registration, and fast numerical algorithms for solving these problems.
Author: Tony F. Chan
Publisher: SIAM
ISBN: 089871589X
Category : Computers
Languages : en
Pages : 414
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Book Description
This book develops the mathematical foundation of modern image processing and low-level computer vision, bridging contemporary mathematics with state-of-the-art methodologies in modern image processing, whilst organizing contemporary literature into a coherent and logical structure. The authors have integrated the diversity of modern image processing approaches by revealing the few common threads that connect them to Fourier and spectral analysis, the machinery that image processing has been traditionally built on. The text is systematic and well organized: the geometric, functional, and atomic structures of images are investigated, before moving to a rigorous development and analysis of several image processors. The book is comprehensive and integrative, covering the four most powerful classes of mathematical tools in contemporary image analysis and processing while exploring their intrinsic connections and integration. The material is balanced in theory and computation, following a solid theoretical analysis of model building and performance with computational implementation and numerical examples.
Author: Kristian Bredies
Publisher: Springer
ISBN: 3030014584
Category : Mathematics
Languages : en
Pages : 481
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Book Description
This book addresses the mathematical aspects of modern image processing methods, with a special emphasis on the underlying ideas and concepts. It discusses a range of modern mathematical methods used to accomplish basic imaging tasks such as denoising, deblurring, enhancing, edge detection and inpainting. In addition to elementary methods like point operations, linear and morphological methods, and methods based on multiscale representations, the book also covers more recent methods based on partial differential equations and variational methods. Review of the German Edition: The overwhelming impression of the book is that of a very professional presentation of an appropriately developed and motivated textbook for a course like an introduction to fundamentals and modern theory of mathematical image processing. Additionally, it belongs to the bookcase of any office where someone is doing research/application in image processing. It has the virtues of a good and handy reference manual. (zbMATH, reviewer: Carl H. Rohwer, Stellenbosch)
Author: Tudor Barbu
Publisher: Springer
ISBN: 3319930060
Category : Computers
Languages : en
Pages : 134
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Book Description
This book covers two essential PDE-based image processing fields: image denoising and image inpainting. It describes the state-of-the-art PDE-based image restoration and interpolation (inpainting) techniques, focusing on the latest advances in PDE-based image processing and analysis, and explores novel techniques involving diffusion-based models and variational schemes. The PDE and variational schemes clearly outperform the conventional approaches in these areas, and can successfully remove image noise and reconstruct missing or highly degraded regions, while preserving the essential features and avoiding unintended effects. The book addresses researchers and graduate students, but is also well suited for professionals in both the mathematics and electrical engineering domains, as it provides rigorous mathematical investigations of the image processing models described, as well as mathematical treatments for the numerical approximation schemes of these differential models.
Author: Evren Özarslan
Publisher: Springer Nature
ISBN: 3030562158
Category : Algebra
Languages : en
Pages : 284
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Book Description
This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28-November 2, 2018.
Author: Roumen Kountchev
Publisher: Springer Nature
ISBN: 9811538638
Category : Technology & Engineering
Languages : en
Pages : 504
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Book Description
This book gathers selected papers presented at the conference “Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology,” one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas. The aim of the conference was to establish a platform for experts to combine their efforts and share their ideas in the related areas in order to promote and accelerate future development. This second volume discusses algorithms and applications, focusing mainly on the following topics: 3D printing technologies; naked, dynamic and auxiliary 3D displays; VR/AR/MR devices; VR camera technologies; microprocessors for 3D data processing; advanced 3D computing systems; 3D data-storage technologies; 3D data networks and technologies; 3D data intelligent processing; 3D data cryptography and security; 3D visual quality estimation and measurement; and 3D decision support and information systems.
Author: Abdelhak Belhi
Publisher: Springer Nature
ISBN: 3030667774
Category : Technology & Engineering
Languages : en
Pages : 288
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Book Description
This book considers the challenges related to the effective implementation of artificial intelligence (AI) and machine learning (ML) technologies to the cultural heritage digitization process. Particular focus is placed on improvements to the data acquisition stage, as well as the data enrichment and curation stages, using advanced artificial intelligence techniques and tools. An emphasis is placed on recent applications related to deep learning for visual recognition, generative models, natural language processing, and super resolution. The book is a valuable reference for researchers working in the multidisciplinary field of cultural heritage and AI, as well as professional experts in the art and culture domains, such as museums, libraries, and historic sites and buildings. Reports on techniques and methods that leverage AI and machine learning and their impact on the digitization of cultural heritage; Addresses challenges of improving data acquisition, enrichment and management processes; Highlights contributions from international researchers from diverse fields and subject areas.
Author: Ke Chen
Publisher: Springer Nature
ISBN: 3030986616
Category : Mathematics
Languages : en
Pages : 1981
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Book Description
This handbook gathers together the state of the art on mathematical models and algorithms for imaging and vision. Its emphasis lies on rigorous mathematical methods, which represent the optimal solutions to a class of imaging and vision problems, and on effective algorithms, which are necessary for the methods to be translated to practical use in various applications. Viewing discrete images as data sampled from functional surfaces enables the use of advanced tools from calculus, functions and calculus of variations, and nonlinear optimization, and provides the basis of high-resolution imaging through geometry and variational models. Besides, optimization naturally connects traditional model-driven approaches to the emerging data-driven approaches of machine and deep learning. No other framework can provide comparable accuracy and precision to imaging and vision. Written by leading researchers in imaging and vision, the chapters in this handbook all start with gentle introductions, which make this work accessible to graduate students. For newcomers to the field, the book provides a comprehensive and fast-track introduction to the content, to save time and get on with tackling new and emerging challenges. For researchers, exposure to the state of the art of research works leads to an overall view of the entire field so as to guide new research directions and avoid pitfalls in moving the field forward and looking into the next decades of imaging and information services. This work can greatly benefit graduate students, researchers, and practitioners in imaging and vision; applied mathematicians; medical imagers; engineers; and computer scientists.
