Multiscale Transforms with Application to Image Processing

Multiscale Transforms with Application to Image Processing PDF

Author: Aparna Vyas

Publisher: Springer

Published: 2017-12-05

Total Pages: 254

ISBN-13: 9811072728

DOWNLOAD EBOOK →

This book provides an introduction to image processing, an overview of the transforms which are most widely used in the field of image processing, and an introduction to the application of multiscale transforms in image processing. The book is divided into three parts, with the first part offering the reader a basic introduction to image processing. The second part of the book starts with a chapter on Fourier analysis and Fourier transforms, wavelet analysis, and ends with a chapter on new multiscale transforms. The final part of the book deals with all of the most important applications of multiscale transforms in image processing. The chapters consist of both tutorial and highly advanced material, and as such the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications. The technique of solving problems in the transform domain is common in applied mathematics and widely used in research and industry, but is a somewhat neglected subject within the undergraduate curriculum. It is hoped that faculty can use this book to create a course that can be offered early in the curriculum and fill this void. Also, the book is intended to be used as a reference manual for scientists who are engaged in image processing research, developers of image processing hardware and software systems, and practising engineers and scientists who use image processing as a tool in their applications.

Mathematical Morphology and Its Applications to Image and Signal Processing

Mathematical Morphology and Its Applications to Image and Signal Processing PDF

Author: Petros Maragos

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 480

ISBN-13: 1461304695

DOWNLOAD EBOOK →

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications

Sparse Image and Signal Processing

Sparse Image and Signal Processing PDF

Author: Jean-Luc Starck

Publisher: Cambridge University Press

Published: 2015-10-14

Total Pages: 449

ISBN-13: 1107088062

DOWNLOAD EBOOK →

Presents state-of-the-art sparse and multiscale image and signal processing with applications in astronomy, biology, MRI, media, and forensics.

Image Processing and Data Analysis

Image Processing and Data Analysis PDF

Author: Jean-Luc Starck

Publisher: Cambridge University Press

Published: 1998

Total Pages: 301

ISBN-13: 0521599148

DOWNLOAD EBOOK →

Powerful techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book provides an in-depth introduction to a range of these innovative, avante-garde data-processing techniques. It develops the reader's understanding of each technique and then shows with practical examples how they can be applied to improve the skills of graduate students and researchers in astronomy, electrical engineering, physics, geophysics and medical imaging. What sets this book apart from others on the subject is the complementary blend of theory and practical application. Throughout, it is copiously illustrated with real-world examples from astronomy, electrical engineering, remote sensing and medicine. It also shows how many, more traditional, methods can be enhanced by incorporating the new wavelet and multiscale methods into the processing. For graduate students and researchers already experienced in image processing and data analysis, this book provides an indispensable guide to a wide range of exciting and original data-analysis techniques.

Digital Signal Processing with Matlab Examples, Volume 2

Digital Signal Processing with Matlab Examples, Volume 2 PDF

Author: Jose Maria Giron-Sierra

Publisher: Springer

Published: 2016-12-02

Total Pages: 913

ISBN-13: 9811025371

DOWNLOAD EBOOK →

This is the second volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification.

Information Technologies in Biomedicine, Volume 3

Information Technologies in Biomedicine, Volume 3 PDF

Author: Ewa Piętka

Publisher: Springer Science & Business

Published: 2014-04-19

Total Pages: 427

ISBN-13: 3319065939

DOWNLOAD EBOOK →

New computerized approaches to various problems have become critically important in healthcare. Computer assisted diagnosis has been extended towards a support of the clinical treatment. Mathematical information analysis, computer applications have become standard tools underpinning the current rapid progress with developing Computational Intelligence. A computerized support in the analysis of patient information and implementation of a computer aided diagnosis and treatment systems, increases the objectivity of the analysis and speeds up the response to pathological changes. This book presents a variety of state-of-the-art information technology and its applications to the networked environment to allow robust computerized approaches to be introduced throughout the healthcare enterprise. Image analysis and its application is the traditional part that deals with the problem of data processing, recognition and classification. Bioinformatics has become a dynamically developed field of computer assisted biological data analysis. This book is a great reference tool for scientists who deal with problems of designing and implementing processing tools employed in systems that assist the radiologists and biologists in patient data analysis.

Knowledge-Oriented Applications in Data Mining

Knowledge-Oriented Applications in Data Mining PDF

Author: Kimito Funatsu

Publisher: BoD – Books on Demand

Published: 2011-01-21

Total Pages: 458

ISBN-13: 9533071540

DOWNLOAD EBOOK →

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.

Artificial Intelligence and Security

Artificial Intelligence and Security PDF

Author: Xingming Sun

Publisher: Springer Nature

Published: 2020-08-31

Total Pages: 841

ISBN-13: 303057881X

DOWNLOAD EBOOK →

This two-volume set LNCS 12239-12240 constitutes the refereed proceedings of the 6th International Conference on Artificial Intelligence and Security, ICAIS 2020, which was held in Hohhot, China, in July 2020. The conference was formerly called “International Conference on Cloud Computing and Security” with the acronym ICCCS. The total of 142 full papers presented in this two-volume proceedings was carefully reviewed and selected from 1064 submissions. The papers were organized in topical sections as follows: Part I: Artificial intelligence and internet of things. Part II: Internet of things, information security, big data and cloud computing, and information processing.

Handbook of Biomedical Image Analysis

Handbook of Biomedical Image Analysis PDF

Author: David Wilson

Publisher: Springer Science & Business Media

Published: 2006-10-28

Total Pages: 661

ISBN-13: 0306485516

DOWNLOAD EBOOK →

Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry . Key Features: - Principles of intra-vascular ultrasound (IVUS) - Principles of positron emission tomography (PET) - Physical principles of magnetic resonance angiography (MRA). - Basic and advanced level set methods - Shape for shading method for medical image analysis - Wavelet transforms and other multi-scale analysis functions - Three dimensional deformable surfaces - Level Set application for CT lungs, brain MRI and MRA volume segmentation - Segmentation of incomplete tomographic medical data sets - Subjective level sets for missing boundaries for segmentation

Stochastic Image Processing

Stochastic Image Processing PDF

Author: Chee Sun Won

Publisher: Springer Science & Business Media

Published: 2013-11-27

Total Pages: 176

ISBN-13: 1441988572

DOWNLOAD EBOOK →

Stochastic Image Processing provides the first thorough treatment of Markov and hidden Markov random fields and their application to image processing. Although promoted as a promising approach for over thirty years, it has only been in the past few years that the theory and algorithms have developed to the point of providing useful solutions to old and new problems in image processing. Markov random fields are a multidimensional extension of Markov chains, but the generalization is complicated by the lack of a natural ordering of pixels in multidimensional spaces. Hidden Markov fields are a natural generalization of the hidden Markov models that have proved essential to the development of modern speech recognition, but again the multidimensional nature of the signals makes them inherently more complicated to handle. This added complexity contributed to the long time required for the development of successful methods and applications. This book collects together a variety of successful approaches to a complete and useful characterization of multidimensional Markov and hidden Markov models along with applications to image analysis. The book provides a survey and comparative development of an exciting and rapidly evolving field of multidimensional Markov and hidden Markov random fields with extensive references to the literature.