First Published in 1997. Routledge is an imprint of Taylor & Francis, an informa company.

This book describes algorithms and hardware implementations of computer holography, especially in terms of fast calculation. It summarizes the basics of holography and computer holography and describes how conventional diffraction calculations play a central role. Numerical implementations by actual codes will also be discussed. This book will explain new fast diffraction calculations, such as scaled scalar diffraction. Computer Holography will also explain acceleration algorithms for computer-generated hologram (CGH) generation and digital holography with 3D objects composed of point clouds, using look-up table- (LUT) based algorithms, and a wave front recording plane. 3D objects composed of polygons using tilted plane diffraction, expressed by multi-view images and RGB-D images, will be explained in this book. Digital holography, including inline, off-axis, Gabor digital holography, and phase shift digital holography, will also be explored. This book introduces applications of computer holography, including phase retrieval algorithm, holographic memory, holographic projection, and deep learning in computer holography, while explaining hardware implementations for computer holography. Recently, several parallel processors have been released (for example, multi-core CPU, GPU, Xeon Phi, and FPGA). Readers will learn how to apply algorithms to these processors. Features Provides an introduction of the basics of holography and computer holography Summarizes the latest advancements in computer-generated holograms Showcases the latest researchers of digital holography Discusses fast CGH algorithms and diffraction calculations, and their actual codes Includes hardware implementation for computer holography, and its actual codes and quasi-codes

Sixty years after its birth, Synthetic Aperture Radar (SAR) evolved as a key player of earth observation, and it is continually upgraded by enhanced hardware functionality and improved overall performance in response to user requirements. The basic information gained by SAR includes the backscattering coefficient of targets, their phases (the truncated distance between SAR and its targets), and their polarization dependence. The spatiotemporal combination of the multiple data operated on the satellite or aircraft significantly increases its sensitivity to detect changes on earth, including temporal variations of the planet in amplitude and the interferometric change for monitoring disasters; deformations caused by earthquakes, volcanic activity, and landslides; environmental changes; ship detection; and so on. Earth-orbiting satellites with the appropriate sensors can detect environmental changes because of their large spatial coverage and availability. Imaging from Spaceborne and Airborne SARs, Calibration, and Applications provides A-to-Z information regarding SAR researches through 15 chapters that focus on the JAXA L-band SAR, including hardware description, principles of SAR imaging, theoretical description of SAR imaging and error, ScanSAR imaging, polarimetric calibration, inflight antenna pattern, SAR geometry and ortho rectification, SAR calibration, defocusing for moving targets, large-scale SAR imaging and mosaic, interferometric SAR processing, irregularities, application, and forest estimation. Sample data are created by using L-band SAR, JERS-1, PALSAR, PALSAR-2, and Pi-SAR-L2. This book is based on the author's experience as a principal researcher at JAXA with responsibilities for L-band SAR operation and researches. It reveals the inside of SAR processing and application researches performed at JAXA, which makes this book a valuable reference for a wide range of SAR researchers, professionals, and students.

Artificial Vision is a rapidly growing discipline, aiming to build computational models of the visual functionalities in humans, as well as machines that emulate them. Visual communication in itself involves a numberof challenging topics with a dramatic impact on contemporary culture where human-computer interaction and human dialogue play a more and more significant role.
This state-of-the-art book brings together carefully selected review articles from world renowned researchers at the forefront of this exciting area. The contributions cover topics including image processing, computational geometry, optics, pattern recognition, and computer science. The book is divided into three sections. Part I covers active vision; Part II deals with the integration of visual with cognitive capabilities; and Part III concerns visual communication.
Artificial Vision will be essential reading for students and researchers in image processing, vision, and computer science who want to grasp the current concepts and future directions of this challenging field.
Key Features
* This state-of-the-art book brings together selected review articles and accounts of current projects from world-renowned researchers at the forefront of this exciting area; The contributions cover topics such as:
* psychology of perception
* image processing
* computational geometry
* visual knowledge representation and languages
* It is this truly multi-disciplinary approach that has produced successful theories and applications for the subject.

This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.

An up-to-date, expert guide to modern digital image databases

This volume presents the state of the art in digital image database design, with a concentration on storage and retrieval techniques, and includes a set of selected application case studies.

Chapters by experts from around the world explore a variety of techniques for accessing images based on color, texture, shape, and semantic descriptions. Underlying principles are stressed, including compression, indexing, storage organization, and transmission.

Image Databases also features detailed coverage of these important issues:

• Hierarchical storage management
• Database support
• Search at multiple abstraction levels
• Content extraction from compressed imagery
• Standards for representation and search

Case studies cover important application areas including:

• Photographic images
• Satellite imagery
• Images in the oil industry
• Medical imagery

A wide range of introductory material and an extensive bibliography makes Image Databases an excellent text for graduate-level students. It also serves as a valuable reference for developers and researchers in the field, and as a guide for helping IT professionals more fully understand the discipline.

Case-based reasoning in design is becoming an important approach to computer-support for design as well as an important component in understanding the design process. Design has become a major focus for problem solving paradigms due to its complexity and open-ended nature. This book presents a clear description of how case-based reasoning can be applied to design problems, including the representation of design cases, indexing and retrieving design cases, and the range of paradigms for adapting design cases. With a focus on design, this book differs from others that provide a generalist view of case-based reasoning.
This volume provides two important contributions to the area:
* a general description of the issues and alternatives in applying case-based reasoning to design, and
* a description of specific implementations of case-based design.
Through this combination, the reader will learn about both the general issues and the practical problems in supporting design through case-based reasoning. This book was prepared to fill a gap in the literature on the unique problems that design introduces to computational paradigms developed in computer science. It also addresses the needs of computational support for design problem solving from both theoretical and practical perspectives.

Sixth in the book series, Advances in Image Communication, which documents the rapid advancements of recent years in image communication technologies, this volume provides a comprehensive exploration of subband coding.

Originally, subband coding and transform coding were developed separately. The former, however, benefitted considerably from the earlier evolution of transform coding theory and practice. Retaining their own terminology and views, the two methods are closely related and this book indeed aims to unify the approaches. Specifically, the volume contributes effectively to the understanding of frequency domain coding techniques. Many images from coding experiments are presented, enabling the reader to consider the properties of different coders.

Chapter 1 introduces the problem of image compression in general terms. Sampling of images and other fundamental concepts, such as entropy and the rate distortion function, are briefly reviewed. The idea of viewing coding techniques as series expansions is also introduced. The second chapter presents signal decomposition and the conditions for perfect reconstruction from minimum representations. Chapter 3 deals with filter bank structures, primarily those displaying the perfect reconstruction property. Quantization techniques and the efficient exploitation of the bit resources are discussed from a theoretical perspective in Chapter 4 and this issue is further examined in Chapter 6, from a more practical point of view. Chapter 5 provides a development of gain formulas, i.e. quantitative measures of the performance of filter banks in a subband coding context, and these are then employed in a search for optimal filter banks. A number of examples of coded images using different subband coders are presented in Chapter 7, these indicating that subband coders give rise to some characteristic types of image degradations. Accordingly, Chapter 8 presents several techniques for minimizing these artifacts. The theory and practice of subband coding of video, at several target bit rates, is discussed in the last chapter.

Spectacular advances during the last decade have altered the related disciplines of computing and telecommunications beyond all recognition. The developments in the"enabling technologies,"which have made these advances possible, have been less obvious to the casual observer. The subject of this book is one of these technologies--the coding of still images and picture sequences (video).
Digital Compression of Still Images and Video is general in approach and covers all the recognized coding algorithms; explaining their basic theory in enough detail that the reader will understand the principles involved. Results which have been achieved with coding algorithms by researchers in all parts of the world are also discussed. A brief historical review of the area is included to orient those new to the field, and the work is supported by references spanning the period from the earliest work on time/frequency analysis, to the latest topic of research interest--image sequence transmission using asynchronous transfer mode (ATM) techniques.
This book will make an excellent reference for graduates and researchers working on image coding and transmission, and will also be of use to those in the related areas of computer vision and multimedia developments. It is essential reading for the rapidly increasing number of technical and professional staff in the industrial environment who, maybe for the first time, are coming to grips with image coding.
Key Features
* Provides complete and up-to-date coverage of all digital image and video coding (compression) techniques
* Includes more than 850 references covering relevant work from the 1940s to the present
* Presents information on new directions in coding
* Contains details on current coding standards
* Describes and explains all algorithms in use for image coding

Providing a wealth of information on fundamental topics in the areas of linear air and underwater acoustics, as well as space-time signal processing, this book provides real-world design and analysis equations. As a consequence of the interdisciplinary nature of air and underwater acoustics, the book is divided into two parts: Acoustic Field Theory and Space-Time Signal Processing. It covers the fundamentals of acoustic wave propagation as well as the fundamentals of aperture theory, array theory, and signal processing. Starting with principles and using a consistent, mainly standard notation, this book develops, in detail, basic results that are useful in a variety of air and underwater acoustic applications. Numerous figures, examples, and problems are included.

The rapid advancements in image communication technologies are documented in the book series, Advances in Image Communication. Each publication provides an in-depth exploration of an intrinsic element of the multi-disciplinary field and together they form a comprehensive overview of the whole.

This volume, the fifth in the series, examines the definition, study and use of the wavelet transform in communications for two-dimensional (2-D) digital signals. The transform is used for signal reorganization before compression and the trade-off between these two steps and the whole compression process is discussed.

The five chapters specifically present the theory of wavelets applied to images, then applications of compression of still images and sequences. Chapter 1 introduces biorthogonal bases of compactly supported wavelets: this generalization of orthonormal wavelet theory allows the use of linear phase filters. A non rectangular wavelet representation of 2-D signals is developed in the second chapter: the properties usually used with wavelets, phase, linearity, and regularity are discussed. Chapter 3 is composed of three parts: a description of commonly used biorthogonal wavelets; a presentation of vector quantization algorithms; a consideration of lattice vector quantization followed by a discussion of the bit allocation procedure (with experimental results given). The fourth chapter deals with a region-based discrete wavelet transform for image coding. Chapter 5 investigates the transmission of image sequences: wavelet transforms and motion estimation are detailed in a multiconstraint approach of image sequence coding.

Image communication technologies have advanced rapidly in recent years and the book series, Advances in Image Communication is dedicated to documenting these developments. Third in the series, this publication contributes as effectively as its forerunners to the multidisciplinary overview afforded by the series as a whole. At the same time, it stands alone as a comprehensive synopsis of its own particular area of interest.

The book specifically explores two complementary topics, namely:

the coding algorithms made to compress the data rate of digital moving-picture sequences (video-telephony, television TV] and high-definition television HDTV]) and

the transmission on Asynchronous Transfer Mode ATM] networks (packet-switching transmission media). It provides an in-depth view of the current state-of-the-art and endeavors to stimulate increasing research efforts for the future.

This unique reference presents in-depth coverage of the latest methods and applications of digital image processing describing various computer architectures ideal for satisfying specific image processing demands.

In the area of Digital Image Processing the new area of "Time-Varying Image Processing and Moving Oject Recognition" is contributing to impressive advances in several fields. Presented in this volume are new digital image processing and recognition methods, implementation techniques and advanced applications such as television, remote sensing, biomedicine, traffic, inspection, and robotics. New approaches (such as digital transforms, neural networks) for solving 2-D and 3-D problems are described. Many papers concentrate on motion estimation and recognition i.e. tracking of moving objects. Overall, the book describes the state-of-the-art (theory, implementation, applications) of this developing area, together with future trends. The work will be of interest not only to researchers, professors and students in university departments of engineering, communications, computers and automatic control, but also to engineers and managers of industries concerned with computer vision, manufacturing, automation, robotics and quality control.

Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.

Optimal and Adaptive Signal Processing covers the theory of optimal and adaptive signal processing using examples and computer simulations drawn from a wide range of applications, including speech and audio, communications, reflection seismology and sonar systems. The material is presented without a heavy reliance on mathematics and focuses on one-dimensional and array processing results, as well as a wide range of adaptive filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS algorithm, applications of adaptive filtering, algorithms and structures for adaptive filtering, spectral analysis, and array signal processing.

Optimal and Adaptive Signal Processing is a valuable guide for scientists and engineers, as well as an excellent text for senior undergraduate/graduate level students in electrical engineering.

The design and construction of three-dimensional 3-D] object recognition systems has long occupied the attention of many computer vision researchers. The variety of systems that have been developed for this task is evidence both of its strong appeal to researchers and its applicability to modern manufacturing, industrial, military, and consumer environments. 3-D object recognition is of interest to scientists and engineers in several different disciplines due to both a desire to endow computers with robust visual capabilities, and the wide applications which would benefit from mature and robust vision systems. However, 3-D object recognition is a very complex problem, and few systems have been developed for actual production use; most existing systems have been developed for experimental use by researchers only. This edited collection of papers summarizes the state of the art in 3-D object recognition using examples of existing 3-D systems developed by leading researchers in the field. While most chapters describe a complete object recognition system, chapters on biological vision, sensing, and early processing are also included. The volume will serve as a valuable reference source for readers who are involved in implementing model-based object recognition systems, stimulating the cross-fertilisation of ideas in the various domains.

The variety of topics on Image Communication is so broad that no one can be a specialist in all the topics, and the whole area is beyond the scope of a single volume, while the requirement of up to date information is ever increasing. This new closed-end book series is intended both as a comprehensive reference for those already active in the area of Image Communication, as well as providing newcomers with a foothold for commencing research. Each volume will comprise a state of the art work on the editor's/author's area of expertise, containing information until now scattered in many journals and proceedings.

Sea Ice Image Processing with MATLAB addresses the topic of image processing for the extraction of key sea ice characteristics from digital photography, which is of great relevance for Artic remote sensing and marine operations. This valuable guide provides tools for quantifying the ice environment that needs to be identified and reproduced for such testing. This includes fit-for-purpose studies of existing vessels, new-build conceptual design and detailed engineering design studies for new developments, and studies of demanding marine operations involving multiple vessels and operational scenarios in sea ice. A major contribution of this work is the development of automated computer algorithms for efficient image analysis. These are used to process individual sea-ice images and video streams of images to extract parameters such as ice floe size distribution, and ice types. Readers are supplied with Matlab source codes of the algorithms for the image processing methods discussed in the book made available as online material. Features Presents the first systematic work using image processing techniques to identify ice floe size distribution from aerial images Helps identify individual ice floe and obtain floe size distributions for Arctic offshore operations and transportation Explains specific algorithms that can be combined to solve various problems during polar sea ice investigations Includes MATLAB (R) codes useful not only for academics, but for ice engineers and scientists to develop tools applicable in different areas such as sustainable arctic marine and coastal technology research Provides image processing techniques applicable to other fields like biomedicine, material science, etc

This book describes the methods and algorithms for image pre-processing and recognition. These methods are based on a parallel shift technology of the imaging copy, as well as simple mathematical operations to allow the generation of a minimum set of features to describe and recognize the image. This book also describes the theoretical foundations of parallel shift technology and pattern recognition. Based on these methods and theories, this book is intended to help researchers with artificial intelligence systems design, robotics, and developing software and hardware applications.

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics.;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.

Presents basic theories, techniques, and procedures used to analyze, design, and implement two-dimensional filters; and surveys a number of applications in image and seismic data processing that demonstrate their use in real-world signal processing. For graduate students in electrical and computer e

Presenting encryption algorithms with diverse characteristics, Image Encryption: A Communication Perspective examines image encryption algorithms for the purpose of secure wireless communication. It considers two directions for image encryption: permutation-based approaches and substitution-based approaches. Covering the spectrum of image encryption principles and techniques, the book compares image encryption with permutation- and diffusion-based approaches. It explores number theory-based encryption algorithms such as the Data Encryption Standard, the Advanced Encryption Standard, and the RC6 algorithms. It not only details the strength of various encryption algorithms, but also describes their ability to work within the limitations of wireless communication systems. Since some ciphers were not designed for image encryption, the book explains how to modify these ciphers to work for image encryption. It also provides instruction on how to search for other approaches suitable for this task. To make this work comprehensive, the authors explore communication concepts concentrating on the orthogonal frequency division multiplexing (OFDM) system and present a simplified model for the OFDM communication system with its different implementations. Complete with simulation experiments and MATLAB (R) codes for most of the simulation experiments, this book will help you gain the understanding required to select the encryption method that best fulfills your application requirements.

In the last few years, biometric techniques have proven their ability to provide secure access to shared resources in various domains. Furthermore, software agents and multi-agent systems (MAS) have shown their efficiency in resolving critical network problems. Iris Biometric Model for Secured Network Access proposes a new model, the IrisCryptoAgentSystem (ICAS), which is based on a biometric method for authentication using the iris of the eyes and an asymmetric cryptography method using "Rivest-Shamir-Adleman" (RSA) in an agent-based architecture. It focuses on the development of new methods in biometric authentication in order to provide greater efficiency in the ICAS model. It also covers the pretopological aspects in the development of the indexed hierarchy to classify DRVA iris templates. The book introduces biometric systems, cryptography, and multi-agent systems (MAS) and explains how they can be used to solve security problems in complex systems. Examining the growing interest to exploit MAS across a range of fields through the integration of various features of agents, it also explains how the intersection of biometric systems, cryptography, and MAS can apply to iris recognition for secure network access. The book presents the various conventional methods for the localization of external and internal edges of the iris of the eye based on five simulations and details the effectiveness of each. It also improves upon existing methods for the localization of the external and internal edges of the iris and for removing the intrusive effects of the eyelids.

Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and Methodologies introduces the fundamentals and applications in the state of the art of rough fuzzy image analysis. In the first chapter, the distinguished editors explain how fuzzy, near, and rough sets provide the basis for the stages of pictorial pattern recognition: image transformation, feature extraction, and classification. The text then discusses hybrid approaches that combine fuzzy sets and rough sets in image analysis, illustrates how to perform image analysis using only rough sets, and describes tolerance spaces and a perceptual systems approach to image analysis. It also presents a free, downloadable implementation of near sets using the Near Set Evaluation and Recognition (NEAR) system, which visualizes concepts from near set theory. In addition, the book covers an array of applications, particularly in medical imaging involving breast cancer diagnosis, laryngeal pathology diagnosis, and brain MR segmentation. Edited by two leading researchers and with contributions from some of the best in the field, this volume fully reflects the diversity and richness of rough fuzzy image analysis. It deftly examines the underlying set theories as well as the diverse methods and applications.

Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing cohesively combines contributions from field experts to deliver a comprehensive account of the latest developments in signal processing. These experts detail the results of their research related to audio and speech enhancement, acoustic image estimation, video compression, biometric recognition, hyperspectral image analysis, tensor decomposition with applications in communications, adaptive sparse-interpolated filtering, signal processing for power line communications, bio-inspired signal processing, seismic data processing, arithmetic transforms for spectrum computation, particle filtering in cooperative networks, three-dimensional television, and more. This book not only shows how signal processing theory is applied in current and emerging technologies, but also demonstrates how to tackle key problems such as how to enhance speech in the time domain, improve audio quality, and meet the desired electrical consumption target for controlling carbon emissions. Signals and Images: Advances and Results in Speech, Estimation, Compression, Recognition, Filtering, and Processing serves as a guide to the next generation of signal processing solutions for speech and video coding, hearing aid devices, big data processing, smartphones, smart digital communications, acoustic sensors, and beyond.