5 edition of **Nonlinear Image Processing (Communications, Networking and Multimedia) (Communications, Networking and Multimedia)** found in the catalog.

- 317 Want to read
- 12 Currently reading

Published
**September 8, 2000** by Academic Press .

Written in English

**Edition Notes**

Contributions | Giovanni Sicuranza (Editor), Sanjit Mitra (Editor) |

The Physical Object | |
---|---|

Number of Pages | 450 |

ID Numbers | |

Open Library | OL7328228M |

ISBN 10 | 0125004516 |

ISBN 10 | 9780125004510 |

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A wide class of nonlinear operators can be devised for image processing applications, based on polynomial and rational functions of the pixels of an image. This chapter shows that this approach can be exploited successfully for image enhancement, image analysis, and image format conversion.

Nonlinear Image Processing by Giovanni L. Sicuranza (Author) ISBN ISBN X. Why is ISBN important. ISBN. This bar-code number lets you verify that you're Nonlinear Image Processing book exactly the right version or edition of a book.

The digit and digit formats both work. Cited by: "The book considers the following filter families, with varying emphasis, according to popularity and impact in image processing tasks: honomorphic filters, relying on a generalized Book Edition: 1.

A widely varied selection of experts provides extensive coverage of nonlinear model-based techniques in image and video processing and analysis. This volume not only details new techniques in still image and digital video but also discusses applications in computer vision, multimedia, and visual information retrieval : Hardcover.

Book Description Nonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical.

Mathematical Nonlinear Image Processing will be of interest to people working in the areas of applied mathematics as well as researchers in computer vision.

Mathematical Nonlinear Image Processing is an edited volume of original research. It has also been published as a special issue of the Journal of Mathematical Imaging Nonlinear Image Processing book Vision. The first book on this topic, relating the new theory to image processing and computer vision applications.

Integrates deep mathematical concepts from various fields into a coherent manuscript with plots, graphs and intuitions, allowing broader access to computer scientists and : Springer International Publishing. This text provides insight into the design of optimal image processing operators for implementation directly into Nonlinear Image Processing book hardware.

Starting with Nonlinear Image Processing book restoration examples and using the minimum of statistics, the book provides a design strategy for a wide range of image processing applications.

Saponara S, Fanucci L and Terreni P () Design of a low-power VLSI macrocell for nonlinear adaptive video noise reduction, EURASIP Nonlinear Image Processing book on Advances in Signal Processing,(), Online publication date: 1-Jan Nonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications.

This book details recent advances in nonlinear theory, techniques, and an array of modern applications. This book details recent advances in nonlinear theory and methods and explores an array of modern signal and image processing applications.

The first several chapters focus on nonlinear signal processing theory, targeting three critical areas: filter analysis, nonlinear filter Price: $ This state-of-the-art book deals with the Nonlinear Image Processing book important aspects of non-linear imaging challenges.

The need for engineering and mathematical methods is essential for defining non-linear effects involved in such areas as computer vision, optical imaging, computer pattern recognition, and. Nonlinear Image Processing book unique text/reference presents a fresh look at nonlinear processing through nonlinear eigenvalue analysis, highlighting how one-homogeneous convex functionals can induce nonlinear operators that can be analyzed within an eigenvalue framework.

The text Cited by: 3. Nonlinear Nonlinear Image Processing book processing | Giovanni Sicuranza, Sanjit Mitra | download | B–OK. Download books for free. Find books. This book details recent advances in nonlinear theory and methods and explores an array of modern signal and image processing applications.

The first several chapters focus on nonlinear signal processing theory, targeting three critical areas: filter analysis. This book can be used either as a textbook in studying applications of wavelets to image processing or as a supplementary resource for studying nonlinear evolution equations or frequency-modulated signals.

Mathematical Nonlinear Image Processing deals with a fast growing research area. The development of the subject springs from two factors: (1) the great expansion of nonlinear methods applied to problems in imaging and vision, and (2) the degree to which nonlinear approaches are both using and fostering new developments in diverse areas of mathematics.

Introduction to nonlinear image processing 14 Perona-Malik Diffusion P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, PAMI F.

Catte, P.L. Lions, J.M. Morel, T. Coll, Image selective smoothing and edge detection by nonlinear diffusion, SIAM J. Numer. Analysis, u(x,y, 0) = u 0(x,y)File Size: 8MB. Topics and features: introduces the classical Fourier transform and its associated operator and energy, and asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processing and computer vision algorithms; describes the properties of the total variation (TV) functional, and how the Manufacturer: Springer.

Get this from a library. Nonlinear image processing. [Sanjit Kumar Mitra; Giovanni L Sicuranza;] -- This state-of-the-art book deals with the most important aspects of non-linear imaging challenges. The need for engineering and mathematical methods is essential for defining non-linear effects.

COVID Resources. Reliable information about the coronavirus (COVID) is available from the World Health Organization (current situation, international travel).Numerous and frequently-updated resource results are available from this ’s WebJunction has pulled together information and resources to assist library staff as they consider how to handle coronavirus.

Publisher Summary This chapter describes the basic tools for digital image processing. The basic tool that is used in designing point operations on digital images is the image histogram. The histogram of the digital image is a plot or graph of the frequency of occurrence of each gray level.

Filtering image data is a standard process used in almost all image processing systems. Nonlinear filters are the most utilized forms of filter construction.

For example, if an image contains a low amount of noise but with relatively high magnitude, then a median filter may be more appropriate.

We present a new method for nonlinear image processing that is well suited for hybrid optical–electronic implementation. An input image is convolved with a long, narrow two-dimensional kernel that is rotated, either continuously or discretely, through deg. During rotation the convolution output is monitored, and the maximum and minimum values measured at each point are stored.

Handbook of Image and Video Processing A volume in Communications, Networking and Multimedia. Book • 2nd Edition • Nonlinear Filtering for Image Analysis and Enhancement.

Gonzalo R. Arce, Jan Bacca and José L. Paredes. this book serves equally well as classroom textbook as reference resource. • Provides practicing engineers. Nonlinear Image Upsampling Method Based on Radial Basis Function Interpolation Article in IEEE Transactions on Image Processing 19(10) May with 78 Reads How we measure 'reads'.

Introduction to nonlinear image processing 43 Further study G. Papandreou and P. Maragos, Multigrid Geometric Active Contour Models,TIP, J. Weickert and B. Romeny, 'Efficient Schemes for Nonlinear Diffusion Filtering', TIP '98 A.

Chambolle, 'An Algorithm for Total Variation Minimization and Applications', JMIV ISBN: OCLC Number: Description: xv, pages: illustrations ; 26 cm. Contents: Analysis and optimization of weighted order statistic and stack filters / S.

Paltmen [and others] --Image enhancement and analysis with weighted medians / G. Arce and J. Paredes --Spatial-rank order selection filters / K. Barner and R. Hardie --Signal-dependent rank-ordered-mean. The first chapter of this book considers image processing, more precisely algorithms of image compression and denoising.

This research is motivated in particular by the new standard for compression of still images known as JPEG The second chapter has new results on the Navier-Stokes and other nonlinear evolution equations.

Digital Image Processing by Stefan G. Stanciu - InTech, This book presents recent advances in digital image processing, with the purpose of providing an insight into the possibilities offered by digital image processing algorithms in various fields.

The text is accompanied by graphical representations. Nonlinear Image Processing (Communications, Networking and Multimedia) eBook: Sicuranza, Giovanni, Mitra, Sanjit: : Kindle StoreAuthor: Giovanni Sicuranza.

For 40 years, Image Processing has been the foundational text for the study of digital image processing. The book is suited for students at the college senior and first-year graduate level with prior background in mathematical analysis, vectors, matrices, probability, statistics, linear systems, and computer : On-line Supplement.

The chapters of this book have thus far mainly addressed binary image processing. While binary image processing is useful in some circumstances, it is very limited in its applications.

The challenge facing nonlinear image processing is to take these methods and extend them to grayscale. This can be done in a number of different : Stephen Marshall. Logic-based nonlinear image processing.

January ; DOI: / S. Marshall; the book provides a design strategy for a wide range of image processing applications. The text is. Chapter Linear Image Processing. Linear image processing is based on the same two techniques as conventional DSP: convolution and Fourier ution is the more important of these two, since images have their information encoded in the spatial domain rather than the frequency domain.

A linear filter is one that can be done with a convolution, which is just the linear sum of values in a sliding window. It can be done equivalently in the Fourier domain by multiplying the spectrum by an image.

Image enhancement is important because of its usefulness in virtually all image processing applications. Image enhancement tools are often classified into (a) point operations, and (b) spatial operators.

Point operations include contrast stretching, noise. The important thing areas coated embrace depth transformations, linear and nonlinear spatial filtering, filtering inside the frequency space, image restoration and registration, color image processing, wavelets, image data compression, morphological image processing, image segmentation, areas and boundary illustration and description, and.

5 Nonlinear Image Processing Techniques Nonlinear Spatial Filters Based on Order Statistics Nonlinear Mean Filters Adaptive Filters The Homomorphic Filter 6 Color Image Processing Color Fundamentals Color Models Examples of Color Image Processing.

After processing, a smooth window is applied to each of the over-lapping segments before they are recombined. This provides a smooth transition of the frequency spectrum from one segment to the next. The second nonlinear technique is called homomorphic signal processing.

This term literally means: the same structure. Addition is not the only. Non-linear filters find application in a range of image pdf and coding applications such as: denoising, edge preserving operations and in some forms of prediction.

For example, the deblocking filters used in the HEVC and H/AVC compression standards are content-adaptive non-linear filters as described in Chapter 9.Download pdf text covers key mathematical principles and algorithms for nonlinear filters used in image processing.

Readers will gain an in-depth understanding of the underlying mathematical and filter design methodologies needed to construct and use nonlinear filters in a variety of applications. The 11 chapters explore topics of contemporary interest as well as fundamentals drawn from nonlinear.Topics and features: introduces the classical Fourier transform and its associated operator and energy, ebook asks how these concepts can be generalized in the nonlinear case; reviews the basic mathematical notion, briefly outlining the use of variational and flow-based methods to solve image-processing and computer vision algorithms; describes.