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Titlebook: Mathematical Problems in Image Processing; Partial Differential Gilles Aubert,Pierre Kornprobst Book 2006Latest edition Springer-Verlag New

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書(shū)目名稱(chēng)Mathematical Problems in Image Processing
副標(biāo)題Partial Differential
編輯Gilles Aubert,Pierre Kornprobst
視頻videohttp://file.papertrans.cn/627/626535/626535.mp4
概述The two most important problems in image analysis, namely image restoration and segmentation, are treated in details and allow to present most of the mathematical concepts useful in this field.Not onl
叢書(shū)名稱(chēng)Applied Mathematical Sciences
圖書(shū)封面Titlebook: Mathematical Problems in Image Processing; Partial Differential Gilles Aubert,Pierre Kornprobst Book 2006Latest edition Springer-Verlag New
描述.Partial differential equations (PDEs) and variational methods were introduced into image processing about fifteen years ago. Since then, intensive research has been carried out. The goals of this book are to present a variety of image analysis applications, the precise mathematics involved and how to discretize them.. .Thus, this book is intended for two audiences. The first is the mathematical community by showing the contribution of mathematics to this domain. It is also the occasion to highlight some unsolved theoretical questions. The second is the computer vision community by presenting a clear, self-contained and global overview of the mathematics involved in image procesing problems. This work will serve as a useful source of reference and inspiration for fellow researchers in Applied Mathematics and Computer Vision, as well as being a basis for advanced courses within these fields.. .During the four years since the publication of the first edition, there has been substantial progress in the range of image processing applications covered by the PDE framework. The main goals of the second edition are to update the first edition by giving a coherent account of some of the rec
出版日期Book 2006Latest edition
關(guān)鍵詞Calculus of Variations; PDE; PDEs in image processing; Partial Differential Equations; Symbol; image anal
版次2
doihttps://doi.org/10.1007/978-0-387-44588-5
isbn_softcover978-1-4419-2182-6
isbn_ebook978-0-387-44588-5Series ISSN 0066-5452 Series E-ISSN 2196-968X
issn_series 0066-5452
copyrightSpringer-Verlag New York 2006
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ion. Different values are appropriate for different datasets and parameter tuning is usually inevitable. A dataset may include simultaneously well-separated and not well-separated classes as well as noise in certain regions of the metric space. Thus, a different . value should be employed depending
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Book 2006Latest editionsearch has been carried out. The goals of this book are to present a variety of image analysis applications, the precise mathematics involved and how to discretize them.. .Thus, this book is intended for two audiences. The first is the mathematical community by showing the contribution of mathematic
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