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Book Quantum Image Processing in Practice

Download or read book Quantum Image Processing in Practice written by Artyom Grigoryan and published by Wiley. This book was released on 2025-02-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive resource addressing the need for a quantum image processing machine learning model that can outperform classical neural networks Quantum Image Processing in Practice explores the transformative potential of quantum color image processing across various domains, including biomedicine, entertainment, economics, and industry. The rapid growth of image data, especially in facial recognition and autonomous vehicles, demands more efficient processing techniques. Quantum computing promises to accelerate digital image processing (DIP) to meet this demand. This book covers the role of quantum image processing (QIP) in quantum information processing, including mathematical foundations, quantum operations, image processing using quantum filters, quantum image representation, and quantum neural networks. It aims to inspire practical applications and foster innovation in this promising field. Topics include: Qubits and Quantum Logic Gates: Introduces qubits, the fundamental data unit in quantum computing, and their manipulation using quantum logic gates like Pauli matrices, rotations, the CNOT gate, and Hadamard matrices. The concept of entanglement, where qubits become interconnected, is also explored, highlighting its importance for applications like quantum teleportation and cryptography. Two and Multiple Qubit Systems: Demonstrates the importance of using two qubits to process color images, enabling image enhancement, noise reduction, edge detection, and feature extraction. Covers the tensor product, Kronecker sum, SWAP gate, and local and controlled gates. Extends to multi-qubit superpositions, exploring local and control gates for three qubits, such as the Toffoli and Fredkin gates, and describes the measurement of superpositions using projection operators. Transforms and Quantum Image Representations: Covers the Hadamard, Fourier, and Heap transforms and their circuits in quantum computation, highlighting their applications in signal and image processing. Introduces the quantum signal-induced heap transform for image enhancement, classification, compression, and filtration. Explores quantum representations and operations for images using the RGB, XYZ, CMY, HSI, and HSV color models, providing numerous examples. Fourier Transform Qubit Representation: Introduces a new model of quantum image representation, the Fourier transform qubit representation. Describes the algorithm and circuit for calculating the 2-D quantum Fourier transform, enabling advancements in quantum imaging techniques. New Operations and Hypercomplex Algebra: Presents new operations on qubits and quantum representations, including multiplication, division, and inverse operations. Explores hypercomplex algebra, specifically quaternion algebra, for its potential in color image processing. Quantum Neural Networks (QNNs): Discusses QNNs and their circuit implementation as advancements in machine learning driven by quantum mechanics. Summarizes various applications of QNNs and current trends and future developments in this rapidly evolving field. The book also addresses challenges and opportunities in QIP research, aiming to inspire practical applications and innovation. It is a valuable resource for researchers, students, and professionals interested in the intersection of quantum computing and color image processing applications, as well as those in visual communications, multimedia systems, computer vision, entertainment, and biomedical applications.

Book Examining Quantum Algorithms for Quantum Image Processing

Download or read book Examining Quantum Algorithms for Quantum Image Processing written by Li, HaiSheng and published by IGI Global. This book was released on 2020-09-25 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: An emerging interdisciplinary field of study in the realm of academia has been quantum computing and its various applications. The rapid rate of progress of this advancing technology as well as its multi-faceted nature has created a vast amount of potential research material for professionals and students in numerous disciplines. Its specific ability to improve upon traditional algorithms for image processing is seizing the attention of researchers in this field, as there remains a lack of exploration into this precise area. Examining Quantum Algorithms for Quantum Image Processing is an essential reference that provides research on quantum Fourier transform, quantum wavelet transform, and quantum wavelet packet transform as tool algorithms in image processing and quantum computing. It provides a comprehensive look into quantum image algorithms to establish frameworks of quantum image processing. While highlighting topics including geometric transformation, quantum compression ratio, and storage circuits, this book is ideally designed for researchers, scientists, developers, academicians, programmers, practitioners, engineers, and upper graduate students.

Book Quantum Image Processing

Download or read book Quantum Image Processing written by Fei Yan and published by Springer Nature. This book was released on 2020-01-03 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to quantum image processing, which focuses on extending conventional image processing tasks to the quantum computing frameworks. It summarizes the available quantum image representations and their operations, reviews the possible quantum image applications and their implementation, and discusses the open questions and future development trends. It offers a valuable reference resource for graduate students and researchers interested in this emerging interdisciplinary field.

Book Quantum Algorithms for Binary Problems with Applications to Image Processing

Download or read book Quantum Algorithms for Binary Problems with Applications to Image Processing written by Natacha Kuete Meli and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Quantum Imaging

    Book Details:
  • Author : Mikhail I. Kolobov
  • Publisher : Springer Science & Business Media
  • Release : 2007-11-03
  • ISBN : 0387339884
  • Pages : 321 pages

Download or read book Quantum Imaging written by Mikhail I. Kolobov and published by Springer Science & Business Media. This book was released on 2007-11-03 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives an overview of the latest progress in the domain of quantum imaging. It reflects three and a half years of research carried out by leading specialists in the area within the Quantum Imaging network, a research programme of the European Community. Quantum Imaging is a newly born branch of quantum optics that investigates the ultimate performance limits of optical imaging allowed by the laws of quantum mechanics. Using the methods and techniques from quantum optics, quantum imaging addresses the questions of image formation, processing and detection with sensitivity and resolution exceeding the limits of classical imaging.

Book Quantum Inspired Meta heuristics for Image Analysis

Download or read book Quantum Inspired Meta heuristics for Image Analysis written by Sandip Dey and published by John Wiley & Sons. This book was released on 2019-08-05 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces quantum inspired techniques for image analysis for pure and true gray scale/color images in a single/multi-objective environment This book will entice readers to design efficient meta-heuristics for image analysis in the quantum domain. It introduces them to the essence of quantum computing paradigm, its features, and properties, and elaborates on the fundamentals of different meta-heuristics and their application to image analysis. As a result, it will pave the way for designing and developing quantum computing inspired meta-heuristics to be applied to image analysis. Quantum Inspired Meta-heuristics for Image Analysis begins with a brief summary on image segmentation, quantum computing, and optimization. It also highlights a few relevant applications of the quantum based computing algorithms, meta-heuristics approach, and several thresholding algorithms in vogue. Next, it discusses a review of image analysis before moving on to an overview of six popular meta-heuristics and their algorithms and pseudo-codes. Subsequent chapters look at quantum inspired meta-heuristics for bi-level and gray scale multi-level image thresholding; quantum behaved meta-heuristics for true color multi-level image thresholding; and quantum inspired multi-objective algorithms for gray scale multi-level image thresholding. Each chapter concludes with a summary and sample questions. Provides in-depth analysis of quantum mechanical principles Offers comprehensive review of image analysis Analyzes different state-of-the-art image thresholding approaches Detailed current, popular standard meta-heuristics in use today Guides readers step by step in the build-up of quantum inspired meta-heuristics Includes a plethora of real life case studies and applications Features statistical test analysis of the performances of the quantum inspired meta-heuristics vis-à-vis their conventional counterparts Quantum Inspired Meta-heuristics for Image Analysis is an excellent source of information for anyone working with or learning quantum inspired meta-heuristics for image analysis.

Book Supervised Learning with Quantum Computers

Download or read book Supervised Learning with Quantum Computers written by Maria Schuld and published by Springer. This book was released on 2018-08-30 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum machine learning investigates how quantum computers can be used for data-driven prediction and decision making. The books summarises and conceptualises ideas of this relatively young discipline for an audience of computer scientists and physicists from a graduate level upwards. It aims at providing a starting point for those new to the field, showcasing a toy example of a quantum machine learning algorithm and providing a detailed introduction of the two parent disciplines. For more advanced readers, the book discusses topics such as data encoding into quantum states, quantum algorithms and routines for inference and optimisation, as well as the construction and analysis of genuine ``quantum learning models''. A special focus lies on supervised learning, and applications for near-term quantum devices.

Book Quantum Computing

    Book Details:
  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release : 2019-04-27
  • ISBN : 030947969X
  • Pages : 273 pages

Download or read book Quantum Computing written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-04-27 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum mechanics, the subfield of physics that describes the behavior of very small (quantum) particles, provides the basis for a new paradigm of computing. First proposed in the 1980s as a way to improve computational modeling of quantum systems, the field of quantum computing has recently garnered significant attention due to progress in building small-scale devices. However, significant technical advances will be required before a large-scale, practical quantum computer can be achieved. Quantum Computing: Progress and Prospects provides an introduction to the field, including the unique characteristics and constraints of the technology, and assesses the feasibility and implications of creating a functional quantum computer capable of addressing real-world problems. This report considers hardware and software requirements, quantum algorithms, drivers of advances in quantum computing and quantum devices, benchmarks associated with relevant use cases, the time and resources required, and how to assess the probability of success.

Book Quantum limited Imaging and Image Processing

Download or read book Quantum limited Imaging and Image Processing written by Optical Society of America and published by . This book was released on 1986 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book New Advances in Intelligent Signal Processing

Download or read book New Advances in Intelligent Signal Processing written by Antonio Ruano and published by Springer Science & Business Media. This book was released on 2011-09-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current volume “New Advances in Intelligent Signal Processing” contains extended works based on a careful selection of papers presented originally at the jubilee sixth IEEE International Symposium on Intelligent Signal Processing (WISP’2009), held in Budapest Hungary, August 26-28, 2009 - celebrating the 10 years anniversary of the WISP event series. The present book does not intent to be an overall survey on the fields of interest of the area, but tries to find topics which represent new, hot, and challenging problems. The book begins with papers investigating selected problems of Modeling, Identification, and Clustering such as fuzzy random variables, evolutionary multi-objective neural network models, a structural learning model of neural networks within a Boltzmann machine, a robust DNA-based clustering techniques, and the advances of combining multi-criteria analysis of signals and pattern recognition using machine learning principles. In the second part of the book Image Processing is treated. The carefully edited chapters deal with fuzzy relation based image enhancement, image contrast control technique based on the application of Łukasiewicz algebra operators, low complexity situational models of image quality improvement, flexible representation of map images to quantum computers, and object recognition in images. The last chapter presents an image processing application for elderly care, performing real-time 3D tracking based on a new evaluative multi-modal algorithm.

Book Remote Sensing and Image Processing in Mineralogy

Download or read book Remote Sensing and Image Processing in Mineralogy written by Maged Marghany and published by CRC Press. This book was released on 2022-03-03 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote Sensing and Image Processing in Mineralogy reveals the critical tools required to comprehend the latest technology surrounding the remote sensing imaging of mineralogy, oil and gas explorations. It particularly focusses on multispectral, hyperspectral and microwave radar, as the foremost sources to understand, analyze and apply concepts in the field of mineralogy. Filling the gap between modern physics quantum theory and image processing applications of remote sensing imaging of geological features, mineralogy, oil and gas explorations, this reference is packed with technical details associated with the potentiality of multispectral, hyperspectral and synthetic aperture radar (SAR). The book also includes key methods needed to extract the value-added information necessary, such as lineaments, gold and copper minings. This book also reveals novel speculation of quantum spectral mineral signature identifications, named as quantized Marghany’s mineral spectral or Marghany Quantum Spectral Algorithms for Mineral identifications (MQSA). Rounding out with practical simulations of 4-D open-pit mining identification and monitoring using the hologram radar interferometry technique, this book brings an effective new source of technology and applications for today’s minerology and petroleum engineers. Key Features • Helps develop new algorithms for retrieving mineral mining potential zones in remote sensing data. • Solves specific problems surrounding the spectral signature libraries of different minerals in multispectral and hyperspectral data. • Includes over 200 equations that illustrate how to follow examples in the book.

Book Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modeling

Download or read book Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modeling written by Maged Marghany and published by Elsevier. This book was released on 2024-07-19 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synthetic Aperture Radar Image Processing Algorithms for Nonlinear Oceanic Turbulence and Front Modelling is both a research- and practice-based reference that bridges the gap between the remote sensing field and the dynamic oceanography exploration field. In this perspective, the book explicates how to apply techniques in synthetic aperture radar and quantum interferometry synthetic aperture radar (QInSAR) for oceanic turbulence and front simulation and modelling. The book includes detailed algorithms to enable readers to better understand and implement the practices covered in their own work and apply QInSAR to their own research.This multidisciplinary reference is useful for researchers and academics in dynamic oceanography and modelling, remote sensing and aquatic science, as well as geographers, geophysicists, and environmental engineers Details the potential of synthetic aperture radar in imaging ocean surface dynamical features Includes detailed algorithms and methods, allowing readers to develop their own computer algorithms Covers the latest applications of quantum image processing

Book Pattern Recognition and Machine Intelligence

Download or read book Pattern Recognition and Machine Intelligence written by Bhabesh Deka and published by Springer Nature. This book was released on 2019-11-25 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set of LNCS 11941 and 11942 constitutes the refereed proceedings of the 8th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2019, held in Tezpur, India, in December 2019. The 131 revised full papers presented were carefully reviewed and selected from 341 submissions. They are organized in topical sections named: Pattern Recognition; Machine Learning; Deep Learning; Soft and Evolutionary Computing; Image Processing; Medical Image Processing; Bioinformatics and Biomedical Signal Processing; Information Retrieval; Remote Sensing; Signal and Video Processing; and Smart and Intelligent Sensors.

Book Introduction to Optical Quantum Information Processing

Download or read book Introduction to Optical Quantum Information Processing written by Pieter Kok and published by Cambridge University Press. This book was released on 2010-04-22 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum information processing offers fundamental improvements over classical information processing, such as computing power, secure communication, and high-precision measurements. However, the best way to create practical devices is not yet known. This textbook describes the techniques that are likely to be used in implementing optical quantum information processors. After developing the fundamental concepts in quantum optics and quantum information theory, the book shows how optical systems can be used to build quantum computers according to the most recent ideas. It discusses implementations based on single photons and linear optics, optically controlled atoms and solid-state systems, atomic ensembles, and optical continuous variables. This book is ideal for graduate students beginning research in optical quantum information processing. It presents the most important techniques of the field using worked examples and over 120 exercises.

Book Advanced Machine Vision Paradigms for Medical Image Analysis

Download or read book Advanced Machine Vision Paradigms for Medical Image Analysis written by Tapan K. Gandhi and published by Academic Press. This book was released on 2020-08-11 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs. Explores major emerging trends in technology which are supporting the current advancement of medical image analysis with the help of computational intelligence Highlights the advancement of conventional approaches in the field of medical image processing Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques, as well as their applications in medical image analysis

Book Progress in Intelligent Computing Techniques  Theory  Practice  and Applications

Download or read book Progress in Intelligent Computing Techniques Theory Practice and Applications written by Pankaj Kumar Sa and published by Springer. This book was released on 2017-08-03 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book focuses on both theory and applications in the broad areas of communication technology, computer science and information security. This two volume book contains the Proceedings of 4th International Conference on Advanced Computing, Networking and Informatics. This book brings together academic scientists, professors, research scholars and students to share and disseminate information on knowledge and scientific research works related to computing, networking, and informatics to discuss the practical challenges encountered and the solutions adopted. The book also promotes translation of basic research into applied investigation and convert applied investigation into practice.