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 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 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.
Quantum computing is revolutionizing every field of knowledge. With advent of affordable quantum computing almost possible the importance and relevance of quantum computing for all the recent research trends cannot be overemphasized. We have already witnessed quantum analogues of most celebrated classical algorithms starting from Shor’s algorithm for integer factorization, Grover’s search algorithms for unstructured database. Quantum Image Processing is an emerging field borne by applying quantum computing techniques to the Image Processing problems. This paper attempts to summarize and review the state of development in the field of Quantum Image Processing. All major quantum computing platforms have been presented, At the end a discussion on the current trends and future possibilities is presented.
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, 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.
The integration of quantum computing into image processing represents a significant advancement in computational technology, offering transformative capabilities that enhance performance, efficiency, and accuracy. This chapter explores hybrid quantum-classical algorithms, focusing on how quantum subroutines can be integrated into classical image processing workflows. A comparative analysis of various quantum image encoding techniques highlights their strengths and limitations, paving the way for optimized applications across diverse fields. Key advantages of quantum-enhanced image processing, such as improved speed in high-resolution data analysis and superior optimization methods, are discussed in relation to real-world applications, including medical imaging and computer vision. The chapter anticipates future developments in quantum technology, emphasizing the need for interdisciplinary collaboration to unlock the full potential of quantum computing in digital image applications. By addressing the critical gaps in current methodologies, this work aims to inspire further research and innovation in the realm of quantum-enhanced image processing.
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.