The technological background established in these early chapters - especially in the production and processing of television images - vividly illuminates the development of the sophisticated image processing employed in contemporary radar, space exploration, and medical radiological imaging. Continuing this integrated approach, the author links the fundamentals of analog telephony to the development of modern digital signal processing in telecommunications and networking. A detailed account of microprocessor technology further integrates the overall picture of the field of contemporary signal and image processing. Logically, the discussion is extended to the aspects of signal processing involved in artificial intelligence and neural networks.
This graduate textbook explains image geometry, and elaborates on image enhancement in spatial and frequency domain, unconstrained and constrained restoration and restoration from projection, and discusses various coding technologies such as predictive coding and transform coding. Rich in examples and exercises, it prepares electrical engineering and computer science students for further studies on image analysis and understanding.
Focusing on feature extraction while also covering issues and techniques such as image acquisition, sampling theory, point operations and low-level feature extraction, the authors have a clear and coherent approach that will appeal to a wide range of students and professionals. - Ideal module text for courses in artificial intelligence, image processing and computer vision - Essential reading for engineers and academics working in this cutting-edge field - Supported by free software on a companion website
Discrete Signals and Inverse Problems examines fundamental concepts necessary to engineers and scientists working with discrete signal processing and inverse problem solving, and places emphasis on the clear understanding of algorithms within the context of application needs. Based on the original ‘Introduction to Discrete Signals and Inverse Problems in Civil Engineering’, this expanded and enriched version: combines discrete signal processing and inverse problem solving in one book covers the most versatile tools that are needed to process engineering and scientific data presents step-by-step ‘implementation procedures’ for the most relevant algorithms provides instructive figures, solved examples and insightful exercises Discrete Signals and Inverse Problems is essential reading for experimental researchers and practicing engineers in civil, mechanical and electrical engineering, non-destructive testing and instrumentation. This book is also an excellent reference for advanced undergraduate students and graduate students in engineering and science.
The first book to offer practical applications of neural networks to solve problems in digital signal processing and imaging. A highly practical book with a minimum of math and a wealth of examples. Disk includes a complete program for training, testing, and using neural networks along with C++ subroutines for all techniques discussed and source for the book's example code.
Electricity is an integral part of life in modern society. It is one form of energy and can be transported and converted into other forms. Throughout the world electricity is used to light homes and streets, cook meals, power computers and run industrial plants. Electricity is so integrated with our way of living that electricity consumption per person is used to measure the levels of economic development of countries. Any disruptions to electricity supply or blackouts will lead to huge financial loss and threats to lives well-being in the community. Electrical engineering is the profession and study of generating, transmitting, controlling and using electrical energy. It offers a wide range of exciting opportunities to those looking for a fulfilling, challenging and professional career. Electrical engineers are the designers of modern electrical machinery, power systems, transportation and communication systems. They work in various sectors of the community as well including the building industry, the manufacturing industry, the construction industry, consultancy services, technology development, education services as well as government. In these volumes, the essential aspects and fundamentals of electrical engineering are presented. In depth knowledge of various areas of electrical engineering are disseminated by learned scholars in their fields. It is hoped that readers will find all the writings comprehensive, informative and interesting. It is further hoped that these fundamentals will assist the readers to study advanced topics in electrical engineering. If the readers are electrical engineers themselves, it is hoped that the articles will broaden their horizon in electrical engineering and provide them with the necessary knowledge to further their profession as electrical engineers.
Whilst other books cover a broad range of topics, Feature Extraction and Image Processing takes one of the prime targets of applied computer vision, feature extraction, and uses it to provide an essential guide to the implementation of image processing and computer vision techniques. Acting as both a source of reference and a student text, the book explains techniques and fundamentals in a clear and concise manner and helps readers to develop working techniques, with usable code provided throughout. The new edition is updated throughout in line with developments in the field, and is revised to focus on mathematical programming in Matlab. - Essential reading for engineers and students working in this cutting edge field - Ideal module text and background reference for courses in image processing and computer vision
This book is written for academic and industry professionals working in the field of sensing, instrumentation and related fields, and is positioned to give a snapshot of the current state of the art in sensing technology, particularly from the applied perspective. The book is intended to give broad overview of the latest developments, in addition to discussing the process through which researchers go through in order to develop sensors, or related systems, which will become more widespread in the future.
In Deciphering Reality: Simulations, Tests, and Designs, Benjamin B. Olshin takes a problem-based approach to the question of the nature of reality. In a series of essays, the book examines the detection of computer simulations from the inside, wrestles with the problem of visual models of reality, explores Daoist conceptions of reality, and offers possible future directions for deciphering reality. The ultimate goal of the book is to provide a more accessible approach, unlike highly complex philosophical works on metaphysics, which are inaccessible to non-academic readers, and overly abstract (and at times, highly speculative) popular works that offer a mélange of physics, philosophy, and consciousness.
