#Image Processing Based On Partial Differential Equations PDF
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by Xue-Cheng Tai Publisher: Springer Science & Business Media Release Date: 2006-11-22 Genre: Computers Pages: 440 pages ISBN 13: 3540332677 ISBN 10: 9783540332671 Format: PDF, ePUB, MOBI, Audiobooks, Kindle
Synopsis : Image Processing Based on Partial Differential Equations written by Xue-Cheng Tai, published by Springer Science & Business Media which was released on 2006-11-22. Download Image Processing Based on Partial Differential Equations Books now! Available in PDF, EPUB, Mobi Format. Proceedings of the International Conference on PDE-Based Image Processing and Related Inverse Problems, CMA, Oslo, August 8-12, 2005 Xue-Cheng Tai, Knut-Andreas Lie, Tony F. Chan, Stanley Osher. An estimate of each initial contour, ... -- 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.
Authors: Xue-Cheng Tai, Knut-Andreas Lie, Tony F. Chan, Stanley Osher
Type: BOOK - Published: 2006-11-22 - Publisher: Springer Science & Business Media
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.
Type: BOOK - Published: 2019-02-06 - Publisher: Springer
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)
Authors: Ming Jiang, Nathan Ida, Alfred K. Louis, Eric Todd Quinto
Categories: Technology & Engineering
Type: BOOK - Published: 2018-09-18 - Publisher: Springer
This book collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.
Type: BOOK - Published: 2007-08-06 - Publisher: Springer Science & Business Media
This book presents topics of science and engineering which occur in nature or are part of daily life. It describes phenomena which are modelled by partial differential equations, relating to physical variables like mass, velocity and energy, etc. to their spatial and temporal variations. The author has chosen topics representing his career-long interests, including the flow of fluids and gases, granular flows, biological processes like pattern formation on animal skins, kinetics of rarified gases and semiconductor devices. Each topic is presented in its scientific or engineering context, followed by an introduction of applicable mathematical models in the form of partial differential equations.
Authors: Tobias Preusser, Robert M. Kirby, Torben Pätz
Type: BOOK - Published: 2017-07-13 - Publisher: Morgan & Claypool Publishers
In image processing and computer vision applications such as medical or scientific image data analysis, as well as in industrial scenarios, images are used as input measurement data. It is good scientific practice that proper measurements must be equipped with error and uncertainty estimates. For many applications, not only the measured values but also their errors and uncertainties, should be—and more and more frequently are—taken into account for further processing. This error and uncertainty propagation must be done for every processing step such that the final result comes with a reliable precision estimate. The goal of this book is to introduce the reader to the recent advances from the field of uncertainty quantification and error propagation for computer vision, image processing, and image analysis that are based on partial differential equations (PDEs). It presents a concept with which error propagation and sensitivity analysis can be formulated with a set of basic operations. The approach discussed in this book has the potential for application in all areas of quantitative computer vision, image processing, and image analysis. In particular, it might help medical imaging finally become a scientific discipline that is characterized by the classical paradigms of observation, measurement, and error awareness. This book is comprised of eight chapters. After an introduction to the goals of the book (Chapter 1), we present a brief review of PDEs and their numerical treatment (Chapter 2), PDE-based image processing (Chapter 3), and the numerics of stochastic PDEs (Chapter 4). We then proceed to define the concept of stochastic images (Chapter 5), describe how to accomplish image processing and computer vision with stochastic images (Chapter 6), and demonstrate the use of these principles for accomplishing sensitivity analysis (Chapter 7). Chapter 8 concludes the book and highlights new research topics for the future.
Type: BOOK - Published: 2017-01-27 - Publisher: Open Dissertation Press
This dissertation, "Partial Differential Equation Based Methods in Medical Image Processing" by Kwok-wing, Anthony, Sum, 岑國榮, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Partial Di(R)erential Equation Based Methods in Medical Image Processing Submitted by Anthony Kwok Wing SUM for the degree of Doctor of Philosophy at The University of Hong Kong in August 2007 Medical image analysis is essential for clinical diagnosis and surgical planning. To cope with the rapid development of modern imaging technologies, there is a continuingneedforadvancedimageprocessingtechniquestoimproveimagequality and automate the analytical processes. The two most important and fundamental image processing techniques required for fully utilizing and e(R)ectively interpreting the acquired images are image segmentation and image ltering. They play an indispensableroleintheentiremedicalimageanalysisprocess. Inthisthesis, image segmentation and ltering methods using partial di(R)erential equation (PDE) are studied and explored. iiIn daily clinical practice, physicians are required to identify anatomical struc- tures from a large number of medical images. This identication process can be aidedbyimagesegmentationtechniques. Inthisthesis, newdevelopmentsinactive contour models are introduced for image segmentation. First, parametric active contoursaredesirabletoextractobjectswithaconnedboundary. Arobustpara- metric active contour model with a novel external force, namely boundary vector eld (BVF), is proposed. This new model is shown to be more ecient than other existing parametric active contour models in terms of ease of initialization, extrac- tion capability and speed. Second, geometric active contour models are found to be well suited for extracting topologically complex objects such as vessels in an- giograms. However, angiograms and other medical images commonly su(R)er from a nonuniform illumination artifact. This artifact induces serious problem in object extraction during image segmentation. Thus, a novel segmentation scheme is pro- posed based on level set methods and incorporating local contrast information in the formulation. This scheme improves the extraction outcomes even if the image su(R)ers from nonuniform illuminations artifacts. Di(R)erent imaging modalities and imaging environments may generate di(R)erent levels of noise during the data acquisition phase. Image ltering is therefore an essential technique for reducing the noise level and improving the visual quality of an image. Anisotropic di(R)usion is a PDE based ltering method, which has found useful practical applications since its introduction. The kernel of an anisotropic iiidi(R)usionmodelisthedi(R)usioncoecient, whichcharacterizestheoverallbehavior of the entire model. In this study, a new class of anisotropic di(R)usion model is formulated and its outstanding performance is demonstrated with experimental results. Itisshownthatbothsignal-to-noise ratio andvisualqualityofthe ltered images using the new di(R)usion model are improved. In summary, several creative and innovative developments of low level image processing techniques are reported in the thesis. These low level techniques are a critical requirement for advanced high level image analysis procedures, and are indispensable for the automation of many medical image analysis tasks. An abstract of exactly 434 words iv DOI: 10.5353/th_b3895862 Subjects: Differential equations, Partial Diagnostic imaging - Mathematical models Image processing - Mathematics
Authors: Aleksandra Gruca, Tadeusz Czachórski, Katarzyna Harezlak, Stanisław Kozielski, Agnieszka Piotrowska
Categories: Technology & Engineering
Type: BOOK - Published: 2017-09-17 - Publisher: Springer
This Proceedings book provides essential insights into the current state of research in the field of human–computer interactions. It presents the outcomes of the International Conference on Man–Machine Interactions (ICMMI 2017), held on October 3–6, 2017, in Cracow, Poland, which offers a unique international platform for researchers and practitioners to share cutting-edge developments related to technologies, algorithms, tools and systems focused on the means by which humans interact and communicate with computers. This book is the 5th edition in the series and includes a unique selection of high-quality, original papers highlighting the latest theoretical and practical research on technologies, applications and challenges encountered in the rapidly evolving new forms of human–machine relationships. Major research topics covered include human–computer interfaces, bio-data analysis and mining, image analysis and signal processing, decision support and expert systems, pattern recognition, algorithms and optimisations, computer networks, and data management systems. As such, the book offers a valuable resource for researchers in academia, industry and other fields whose work involves man–machine interactions.
Authors: Otmar Scherzer, Markus Grasmair, Harald Grossauer, Markus Haltmeier, Frank Lenzen
Type: BOOK - Published: 2008-10-09 - Publisher: Springer Science & Business Media
This book is devoted to the study of variational methods in imaging. The presentation is mathematically rigorous and covers a detailed treatment of the approach from an inverse problems point of view. Many numerical examples accompany the theory throughout the text. It is geared towards graduate students and researchers in applied mathematics. Researchers in the area of imaging science will also find this book appealing. It can serve as a main text in courses in image processing or as a supplemental text for courses on regularization and inverse problems at the graduate level.
Authors: Xue-Cheng Tai, Knut Morken, Marius Lysaker, Knut-Andreas Lie
Type: BOOK - Published: 2009-05-25 - Publisher: Springer Science & Business Media
This book constitutes the refereed proceedings of the Second International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2009, emanated from the joint edition of the 5th International Workshop on Variational, Geometric and Level Set Methods in Computer Vision, VLSM 2009 and the 7th International Conference on Scale Space and PDE Methods in Computer Vision, Scale-Space 2009, held in Voss, Norway in June 2009. The 71 revised full papers presented were carefully reviewed and selected numerous submissions. The papers are organized in topical sections on segmentation and detection; image enhancement and reconstruction; motion analysis, optical flow, registration and tracking; surfaces and shapes; scale space and feature extraction.
Authors: Jean-François Aujol, Mila Nikolova, Nicolas Papadakis
Type: BOOK - Published: 2015-04-27 - Publisher: Springer
This book constitutes the refereed proceedings of the 5th International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2015, held in Lège-Cap Ferret, France, in May 2015. The 56 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in the following topical sections: scale space and partial differential equation methods; denoising, restoration and reconstruction, segmentation and partitioning; flow, motion and registration; photography, texture and color processing; shape, surface and 3D problems; and optimization theory and methods in imaging.
Type: BOOK - Published: 2021-10-28 - Publisher: Springer Nature
This book constitutes the refereed proceedings of the 16th Conference on Image and Graphics Technologies and Applications, IGTA 2021, held in Beijing, China in June, 2021. The 21 papers presented were carefully reviewed and selected from 86 submissions. They provide a forum for sharing progresses in the areas of image processing technology; image analysis and understanding; computer vision and pattern recognition; big data mining, computer graphics and VR, as well as image technology applications. The volume contains the following thematic blocks: image processing and enhancement techniques (image information acquisition, image/video coding, image/video transmission, image/video storage, compression, completion, dehazing, reconstruction and display, etc.); biometric identification techniques (biometric identification and authentication techniques including face, fingerprint, iris and palm-print, etc.); machine vision and 3D reconstruction (visual information acquisition, camera calibration, stereo vision, 3D reconstruction, and applications of machine vision in industrial inspection, etc.); image/video big data analysis and understanding (object detection and recognition, image/video retrieval, image segmentation, matching, analysis and understanding); computer graphics (modeling, rendering, algorithm simplification and acceleration techniques, realistic scene generation, 3D reconstruction algorithm, system and application, etc.); virtual reality and human-computer interaction (virtual scene generation techniques, tracing and positioning techniques for large-scale space, augmented reality techniques, human-computer interaction techniques based on computer vision, etc.); applications of image and graphics (image/video processing and transmission, biomedical engineering applications, information security, digital watermarking, text processing and transmission, remote sensing, telemetering, etc.); other research works and surveys related to the applications of image and graphics technology.