Quantum theory is one of the prominent progresses in physics in last century. This paper focuses on advances in signal and image processing methods based on quantum theory. Firstly, some basic quantum theoretical concepts are introduced. Then, quantum signal processing, quantum neural network and quantum image processing are discussed separately. Quantum signal processing is stressed since it is a different branch from others in quantum information theory. It only employs the idea of quantum measurement in signal processing but need not fulfill the algorithms on quantum computers. Several applications of quantum signal processing are discussed here. At last, the prospects in this area are described.
Quantum theory is one of the prominent progresses in physics in last century. This paper focuses on advances in signal and image processing methods based on quantum theory. Firstly, some basic quantum theoretical concepts are introduced. Then, quantum signal processing, quantum neural network and quantum image processing are discussed separately. Quantum signal processing is stressed since it is a different branch from others in quantum information theory. It only employs the idea of quantum measurement in signal processing but need not fulfill the algorithms on quantum computers. Several applications of quantum signal processing are discussed here. At last, the prospects in this area are described.
Quantum computation and quantum information is a new research field and interdiscipline of physics,mathematics,computer and information sciences.It is a wonderful combination of the theory of quantum mechanics and classical computation.It has been concerned by many national governments and research groups.Algorithm is the kernel of classical computation as well known,and this situation is the same to quantum computation.Currently,the most representative algorithms are only two.One is Shor's algorithm.The other is Grover's algorithm.The fast computation of set operation is very important,and it is the base of many aspects of sciences and techniques,such as database operation,image processing,signal processing.But,for the set with high-dimension unsorted vectors,the classical electronic computer can do nothing for the requirement of fast computation.Therefore,the new computation principle and new algorithm will be needed for set operations.Quantum image processing is a progress that uses quantum computer to process image and wants to get a better result than that of the electronic computer.It is a new born topic,which will be a hot research topic in the future.This paper presents a comprehensive statementabout quantum algorithm,quantum set operation,quantum image processing and quantum Hopfield neural network.
Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing.This paper starts with a brief review of the principles which underlie quantum computing, and also deals with some of the basics of qubits and quantum computing.Then this paper starts to deal with some different methods of image storage, representation and retrieval in a quantum system.This paper also describes the advantages of using those methods in quantum systems compare to classical systems. In the next section, a short discussion on some of the important aspects, comparison among them and applications of quantum image processing is presented. A few other hot topics and open problems in quantum image processing are mentioned in this paper. This review article will provide the readership an overview of progress witnessed in the area of Quantum Image processing while also simulating further interest to pursue more advanced research in it.
Image processing is one of the many computer domains that has seen quantum computing emerge as a revolutionary technology. This is due to the fact that quantum computing holds the potential of exponential speedups and unique techniques. The purpose of this study is to give a thorough analysis of the applications of quantum computing in image processing. It investigates the ways in which quantum algorithms and hardware might be used to handle traditional issues, such as picture compression, enhancement, pattern detection, and image recovery. Within the scope of this study, the theoretical underpinnings of quantum computing are investigated, recent developments in the field are discussed, and a comparison is made between quantum techniques and classical procedures. In addition to this, it outlines the primary obstacles, such as scalability and hardware limits, that are now preventing the broad use of quantum approaches in image processing. In conclusion, the study provides an overview of prospective future research areas, focusing on the possibility of further integrating quantum computing with sophisticated image processing technologies such as deep learning. The purpose of this work is to provide scholars and practitioners who are interested in the interface of quantum computing and image processing with a basic reference that they may use.
Quantum computing is a promising technology that has the potential to revolutionize many areas of science and technology, including communication. In this review, we discuss the current state of quantum computing in communication and its potential applications in various areas such as network optimization, signal processing, and machine learning for communication. First, the basic principle of quantum computing, quantum physics systems, and quantum algorithms are analyzed. Then, based on the classification of quantum algorithms, several important basic quantum algorithms, quantum optimization algorithms, and quantum machine learning algorithms are discussed in detail. Finally, the basic ideas and feasibility of introducing quantum algorithms into communications are emphatically analyzed, which provides a reference to address computational bottlenecks in communication networks.
The theoretical, experimental and technological areas covering the use of quantum mechanics for communication and computation.Quantum information processing includes investigations in quantum information theory, quantum communication, quantum computation, quantum algorithms and their complexity, and quantum control.The science of quantum information processing is a highly interdisciplinary field.In the context of mathematics it is stimulating research in pure mathematics (e.g.coding theory, *algebras, quantum topology) as well as requiring and providing many opportunities for applied mathematics.The science of quantum information processing emerged from the recognition that usable notions of information need to be physically implementable.In the 1960s and 1970s researchers such as R. Landauer, C. Bennett, C. Helstrom and A. Holevo realized that the laws of physics give rise to fundamental constraints on the ability to implement and manipulate information.Landauer repeatedly stated that "information is physical", providing impetus to the idea that it should be possible to found theories of information on the laws of physics.This is in contrast to the introspective approach which led to the basic definitions of computer science and information theory as formulated by A. Church, A. Turing, C. Shannon and others in the first half of the 20th century.Early work in studying the physical foundations of information focused on the effects of energy limitations and the need for dissipating heat in computation and communication.Beginning with S. Wiesner's work on applications of quantum mechanics to cryptography in the late 1960s, it was realized that there may be intrinsic advantages to using quantum physics in information processing.Quantum cryptography and quantum communication in general were soon established as interesting and non-trivial extensions of classical communication based on bits.That quantum mechanics may be used to improve the efficiency of algorithms was first realized when attempts at simulating quantum mechanical systems resulted in exponentially complex algorithms compared to the physical resources associated with the system simulated.In the 1980s, P. Benioff and R. Feynman introduced the idea of a quantum computer for efficiently implementing quantum physics simulations.Models of quantum computers were developed by D. Deutsch, leading to the formulation of artificial problems that could be solved more efficiently by quantum than by classical computers.The advantages of quantum computers became widely recognized when P.
This paper introduced quantum system theory and researched the theoretical frame of quantum signal processing which simulated the quantum system.It proposed the algorithms in the area of signal processing and image processing based on the frame of quantum signal processing,and constructed general model of quantum algorithm according to the theoretical frame of quantum signal processing.Parallel characteristic was a kind of important characteristic of quantum algorithm so it provided a new method to parallelize the ordinary algorithms.