Image and signal processing techniques are receiving increasing interest because of their numerous real-world applications. Data is now available in different forms, different wavelengths, and even in different dimensions, creating the need for novel multidisciplinary solutions for automated data processing and analysis. Applied Signal and Image Processing: Multidisciplinary Advancements highlights the growing multidisciplinary nature of signal and image processing by focusing on emerging applications and recent advances in well-established fields. This book covers state-or-the-art applications in both signal and image processing, which include optical communication and sensing, wireless communication management, face recognition and facial imaging, solar imaging and feature detection, fractal analysis, and video processing.
Optical remote sensing relies on exploiting multispectral and hyper spectral imagery possessing high spatial and spectral resolutions respectively. These modalities, although useful for most remote sensing tasks, often present challenges that must be addressed for their effective exploitation. This book presents current state-of-the-art algorithms that address the following key challenges encountered in representation and analysis of such optical remotely sensed data. Challenges in pre-processing images, storing and representing high dimensional data, fusing different sensor modalities, pattern classification and target recognition, visualization of high dimensional imagery.
Shrinking pixel sizes along with improvements in image sensors, optics, and electronics have elevated DSCs to levels of performance that match, and have the potential to surpass, that of silver-halide film cameras. Image Sensors and Signal Processing for Digital Still Cameras captures the current state of DSC image acquisition and signal processing technology and takes an all-inclusive look at the field, from the history of DSCs to future possibilities. The first chapter outlines the evolution of DSCs, their basic structure, and their major application classes. The next few chapters discuss high-quality optics that meet the requirements of better image sensors, the basic functions and performance parameters of image sensors, and detailed discussions of both CCD and CMOS image sensors. The book then discusses how color theory affects the uses of DSCs, presents basic image processing and camera control algorithms and examples of advanced image processing algorithms, explores the architecture and required performance of signal processing engines, and explains how to evaluate image quality for each component described. The book closes with a look at future technologies and the challenges that must be overcome to realize them. With contributions from many active DSC experts, Image Sensors and Image Processing for Digital Still Cameras offers unparalleled real-world coverage and opens wide the door for future innovation.
A Unique, Cutting-Edge Approach to Optical Filter Design With more and more information being transmitted over fiber-optic lines, optical filtering has become crucial to the advanced functionality of today's communications networks. Helping researchers and engineers keep pace with this rapidly evolving technology, this book presents digital processing techniques for optical filter design. This higher-level approach focuses on filter characteristics and enables readers to quickly calculate the filter response as well as tackle larger and more complex filters. The authors incorporate numerous theoretical and experimental results from the literature and discuss applications to a variety of systems-including the new wavelength division multiplexing (WDM) technology, which is fast becoming the preferred method for system upgrade and expansion. Special features of this book include: * The theory underlying various architectures that can approximate any filter function * Filter design techniques applicable to a broad range of materials systems-from silica to fiber to microelectromechanical (MEM) systems * Design examples relevant to filters for WDM systems and planar waveguide devices * 250 figures as well as problem sets for use in graduate-level studies
The research and exploitation of optoelectronic properties in the industrial branch of electronics is becoming more popular each day due to the important role they play in the development of a large variety of sensors, devices, and systems for identifying, measuring, and constructing. While optoelectronics study the applications of electronic devices that source, detect, and transform light, machine vision generates and detects light in order to provide imaging-based automatic inspections and analysis for such applications as automatic object and environmental inspection, process control, and robot/mobile machine guidance in industry. Machine vision is less efficient without optoelectronics, and thus, it is important to investigate the theoretical approaches to different optoelectronic devices available for machine vision as well as current scanning technologies. Examining Optoelectronics in Machine Vision and Applications in Industry 4.0 focuses on the examination of emerging technologies for the design, fabrication, and implementation of optoelectronic sensors, devices, and systems in a machine vision approach to support industrial, commercial, and scientific applications. The book covers topics such as the design, fabrication, and implementation of sensors and devices as well as the development viewpoint of optoelectronic systems and artificial vision techniques using optoelectronic devices. The interaction and informational communication between all these mentioned devices in the complex solution of the same task is the subject of modern challenges in Industry 4.0. Thus, this book supports engineers, technology developers, academicians, researchers, and students who seek machine vision techniques for detection, measurement, and 3D reconstruction.
Optical Signal Processing is a collection of synopses of the works of many experts in the different fields of optical signal processing. The book also includes systems or algorithms that have been successfully tried and used. The monograph is divided into seven parts. Part I discusses color image processing and white-light Fourier transformations, while Part II covers topics related to pattern recognition such as optical feature extraction and unconventional correlators. Part III deals with temporal signal processing and its related optical architectures, acoustooptic synthetic aperture radar processors, and acoustooptic signal processors. Part IV tackles nonlinear optical processors and waveguide devices. Part V discusses optical and tomographic transformation. Part VI deals with optical numeric processing, optical linear algebra processors, and related algorithm and software. Part VII talks about devices and components and their applications such as fiber-optic delay-line signal processors and spatial light modulators. The text is recommended for engineers and scientists in the field of optical signal processing, especially those who would like to know more of its advancements.
This book presents the principles and applications of optical fiber communication based on digital signal processing (DSP) for both single and multi-carrier modulation signals. In the context of single carrier modulation, it describes DSP for linear and nonlinear optical fiber communication systems, discussing all-optical Nyquist modulation signal generation and processing, and how to use probabilistic and geometrical shaping to improve the transmission performance. For multi-carrier modulation, it examines DSP-based OFDM signal generation and detection and presents 4D and high-order modulation formats. Lastly, it demonstrates how to use artificial intelligence in optical fiber communication. As such it is a useful resource for students, researches and engineers in the field of optical fiber communication.
Classical and modern theories have given us a degree of noise immunity by defining the sufficient statistic of the mean of the likelihood function. The generalized theory moves beyond these limitations to determine the jointly sufficient statistics of the mean and variance of the likelihood function. Signal and Image Processing in Navigational Systems introduces us to the generalized approach, and then delves rigorously into the theory and practical applications of this approach. This volume represents the most in-depth discussion of the generalized approach to date, providing many examples and computer models to demonstrate how this approach raises the upper limits of noise immunity for navigation systems, leading to better detection performances. This book is vital for signal and image processing experts, radar, communications, acoustics, and navigational systems designers, as well as professionals in the fields of statistical pattern recognition, biomedicine, astronomy, and robotics who wish to extend the boundaries of noise immunity and improve qualitative performance of their systems.
Part of the SPIE/IEEE Series on Imaging Science and Engineering. This book provides a framework for understanding the ensemble of temporal, spatial, and higher-dimensional processes in science and engineering that vary randomly in observations. Suitable as a text for undergraduate and graduate students with a strong background in probability and as a graduate text in image processing courses.
