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 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 via the quantum platform is an emerging area for researchers. Researchers are more interested to move on towards quantum image processing instead of classical image processing. This chapter starts with the review of different quantum image computing-based research papers with a brief idea of the ethics which inspire quantum computing in the background and focus on the current scenario of recent trends of quantum image representation, pitfalls, and summarization of the pros and cons of it, with the limitations of the technologies used and focus on the recent work to be going on and application of it in a different field. In the next, it will focus on the different methods used by the researcher in the previous papers. The next section discussed the different methods based on quantum image representation used. Some different techniques of image storage, retrieval, and representation in a quantum system are discussed. Also, this chapter briefs the pros and cons of using different techniques in quantum systems in comparison to classical systems.
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.
Image processing plays a crucial role in our day to day life as it is helpful to solve important problems in real world. Recent progress in quantum information and computation led to the birth of a new field called Quantum Image Processing. This new field of image processing in quantum domain focuses on the development of the quantum image processing algorithms, which can run more efficiently on quantum computer. These quantum algorithms are better in terms of Image storage and retrieval with reduced computational complexity. In this article we present recent advancements in quantum image representation with different mathematical models and with their corresponding computational complexity.
Efficient and reliable storage, analysis, and transmission of medical images are imperative for accurate diagnosis, treatment, and management of various diseases. Since quantum computing can revolutionize big data analytics by providing faster solutions and security tactics, numerous studies in this field have focused on the use of quantum and quantum-inspired algorithms to enhance the performance of traditional medical image processing approaches. This review aims to provide readers with a succinct yet adequate compendium of the advances in medical image processing combined with quantum behaviors for disease diagnosis and medical image security. Some open challenges are outlined, identifying the performance limitations of current quantum technology in their applications, while addressing the short-, medium-, and long-term development plans of this field in designing future quantum healthcare systems. We hope that this review will provide full guidance for upcoming researchers interested in this area and will stimulate further appetite of experts already active in this area aimed at the pursuit of more advanced quantum paradigms in medical image processing applications.
The tremendous parallel processing capability of quantum computers allow quantum image processing, a multidisciplinary field combining image processing and quantum computing, to expand the potential outcomes for image processing. The problem of quantum computation is to create effective quantum algorithms since quantum computers need extremely effective algorithms than classical algorithm. Additionally, information storage, communication, and computing power are increasing in relevance with the number and importance of processing digital images. Some of these issues might be resolved by encoding the visual data in quantum-mechanical systems as opposed to classical methods and by switching from classical to quantum information processing. Moreover, the quantum image processing is analysed based on the recent research works and is summarized. This study projects the application of quantum image processing and challenges.
Quantum computing, with its promise of exponential speedups and novel algorithms, has emerged as a revolutionary technology in various computational fields, including image processing. This survey provides a comprehensive review of the applications of quantum computing in image processing, exploring how quantum algorithms and hardware can address classical challenges such as image compression, enhancement, pattern recognition, and image recovery. The paper delves into the theoretical foundations of quantum computing, discusses current advancements, and compares quantum methods with traditional approaches. Moreover, it identifies the key challenges, such as scalability and hardware limitations, that currently hinder the widespread adoption of quantum techniques in image processing. Finally, the survey outlines future research directions, highlighting the potential for further integration of quantum computing with advanced image processing technologies like deep learning. This work aims to serve as a foundational reference for researchers and practitioners interested in the intersection of quantum computing and image processing.