Multiscale Transforms with Application to Image Processing

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Publisher : Springer
ISBN 13 : 9811072728
Total Pages : 254 pages
Book Rating : 4.27/5 ( download)

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Book Synopsis Multiscale Transforms with Application to Image Processing by : Aparna Vyas

Download or read book Multiscale Transforms with Application to Image Processing written by Aparna Vyas and published by Springer. This book was released on 2017-12-05 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

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Publisher : Springer Science & Business Media
ISBN 13 : 1461304695
Total Pages : 480 pages
Book Rating : 4.92/5 ( download)

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Book Synopsis Mathematical Morphology and Its Applications to Image and Signal Processing by : Petros Maragos

Download or read book Mathematical Morphology and Its Applications to Image and Signal Processing written by Petros Maragos and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Digital Signal Processing with Matlab Examples, Volume 2

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Publisher : Springer
ISBN 13 : 9811025371
Total Pages : 913 pages
Book Rating : 4.72/5 ( download)

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Book Synopsis Digital Signal Processing with Matlab Examples, Volume 2 by : Jose Maria Giron-Sierra

Download or read book Digital Signal Processing with Matlab Examples, Volume 2 written by Jose Maria Giron-Sierra and published by Springer. This book was released on 2016-12-02 with total page 913 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Sparse Image and Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 1107088062
Total Pages : 449 pages
Book Rating : 4.61/5 ( download)

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Book Synopsis Sparse Image and Signal Processing by : Jean-Luc Starck

Download or read book Sparse Image and Signal Processing written by Jean-Luc Starck and published by Cambridge University Press. This book was released on 2015-10-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents state-of-the-art sparse and multiscale image and signal processing with applications in astronomy, biology, MRI, media, and forensics.

Wavelet Transforms

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Publisher : CRC Press
ISBN 13 : 100077161X
Total Pages : 502 pages
Book Rating : 4.19/5 ( download)

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Book Synopsis Wavelet Transforms by : Firdous A. Shah

Download or read book Wavelet Transforms written by Firdous A. Shah and published by CRC Press. This book was released on 2022-11-28 with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelet Transforms: Kith and Kin serves as an introduction to contemporary aspects of time-frequency analysis encompassing the theories of Fourier transforms, wavelet transforms and their respective offshoots. This book is the first of its kind totally devoted to the treatment of continuous signals and it systematically encompasses the theory of Fourier transforms, wavelet transforms, geometrical wavelet transforms and their ramifications. The authors intend to motivate and stimulate interest among mathematicians, computer scientists, engineers and physical, chemical and biological scientists. The text is written from the ground up with target readers being senior undergraduate and first-year graduate students and it can serve as a reference for professionals in mathematics, engineering and applied sciences. Features Flexibility in the book’s organization enables instructors to select chapters appropriate to courses of different lengths, emphasis and levels of difficulty Self-contained, the text provides an impetus to the contemporary developments in the signal processing aspects of wavelet theory at the forefront of research A large number of worked-out examples are included Every major concept is presented with explanations, limitations and subsequent developments, with emphasis on applications in science and engineering A wide range of exercises are incoporated in varying levels from elementary to challenging so readers may develop both manipulative skills in theory wavelets and deeper insight Answers and hints for selected exercises appear at the end The origin of the theory of wavelet transforms dates back to the 1980s as an outcome of the intriguing efforts of mathematicians, physicists and engineers. Owing to the lucid mathematical framework and versatile applicability, the theory of wavelet transforms is now a nucleus of shared aspirations and ideas.

Computational Intelligence Methods for Super-Resolution in Image Processing Applications

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Publisher : Springer Nature
ISBN 13 : 3030679217
Total Pages : 308 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Computational Intelligence Methods for Super-Resolution in Image Processing Applications by : Anand Deshpande

Download or read book Computational Intelligence Methods for Super-Resolution in Image Processing Applications written by Anand Deshpande and published by Springer Nature. This book was released on 2021-05-28 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the application of deep learning techniques within a particularly difficult computational type of computer vision (CV) problem ─ super-resolution (SR). The authors present and discuss ways to apply computational intelligence (CI) methods to SR. The volume also explores the possibility of using different kinds of CV techniques to develop and enhance the tools/processes related to SR. The application areas covered include biomedical engineering, healthcare applications, medicine, histology, and material science. The book will be a valuable reference for anyone concerned with multiple multimodal images, especially professionals working in remote sensing, nanotechnology and immunology at research institutes, healthcare facilities, biotechnology institutions, agribusiness services, veterinary facilities, and universities.

Sparse Image and Signal Processing

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Publisher : Cambridge University Press
ISBN 13 : 1316483304
Total Pages : 449 pages
Book Rating : 4.05/5 ( download)

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Book Synopsis Sparse Image and Signal Processing by : Jean-Luc Starck

Download or read book Sparse Image and Signal Processing written by Jean-Luc Starck and published by Cambridge University Press. This book was released on 2015-10-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

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Publisher : Academic Press
ISBN 13 : 0128180056
Total Pages : 218 pages
Book Rating : 4.51/5 ( download)

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Book Synopsis Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis by : Nilanjan Dey

Download or read book Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis written by Nilanjan Dey and published by Academic Press. This book was released on 2019-07-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply classification techniques to a wide variety of clinical applications that are appropriate for researchers and biomedical engineers in the areas of machine learning, deep learning, data analysis, data management and computer-aided diagnosis (CAD) systems design. The book covers several complex image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), Bayesian Networks (BN) and deep learning. Further, numerous data mining techniques are discussed, as they have proven to be good classifiers for medical images. Examines the methodology of classification of medical images that covers the taxonomy of both supervised and unsupervised models, algorithms, applications and challenges Discusses recent advances in Artificial Neural Networks, machine learning, and deep learning in clinical applications Introduces several techniques for medical image processing and analysis for CAD systems design

Sparse and Redundant Representations

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Publisher : Springer Science & Business Media
ISBN 13 : 1441970118
Total Pages : 376 pages
Book Rating : 4.14/5 ( download)

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Book Synopsis Sparse and Redundant Representations by : Michael Elad

Download or read book Sparse and Redundant Representations written by Michael Elad and published by Springer Science & Business Media. This book was released on 2010-08-12 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: A long long time ago, echoing philosophical and aesthetic principles that existed since antiquity, William of Ockham enounced the principle of parsimony, better known today as Ockham’s razor: “Entities should not be multiplied without neces sity. ” This principle enabled scientists to select the ”best” physical laws and theories to explain the workings of the Universe and continued to guide scienti?c research, leadingtobeautifulresultsliketheminimaldescriptionlength approachtostatistical inference and the related Kolmogorov complexity approach to pattern recognition. However, notions of complexity and description length are subjective concepts anddependonthelanguage“spoken”whenpresentingideasandresults. The?eldof sparse representations, that recently underwent a Big Bang like expansion, explic itly deals with the Yin Yang interplay between the parsimony of descriptions and the “language” or “dictionary” used in them, and it became an extremely exciting area of investigation. It already yielded a rich crop of mathematically pleasing, deep and beautiful results that quickly translated into a wealth of practical engineering applications. You are holding in your hands the ?rst guide book to Sparseland, and I am sure you’ll ?nd in it both familiar and new landscapes to see and admire, as well as ex cellent pointers that will help you ?nd further valuable treasures. Enjoy the journey to Sparseland! Haifa, Israel, December 2009 Alfred M. Bruckstein vii Preface This book was originally written to serve as the material for an advanced one semester (fourteen 2 hour lectures) graduate course for engineering students at the Technion, Israel.

Image Processing and Data Analysis

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Publisher : Cambridge University Press
ISBN 13 : 0521599148
Total Pages : 301 pages
Book Rating : 4.46/5 ( download)

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Book Synopsis Image Processing and Data Analysis by : Jean-Luc Starck

Download or read book Image Processing and Data Analysis written by Jean-Luc Starck and published by Cambridge University Press. This book was released on 1998 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.