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IMPLEMENTATION OF QUANTUM IMAGE HALFTONING ALGORITHM

Anastasia Monika Oktorianti, Achmad Benny Mutiara, Rina Refianti

Published Jan 1, 2014• 0 citations
Publisher

Abstract

Developing new computing methods and signal processing algorithms by borrowing from the principle of quantum mechanics is a very interesting and new research topic. By utilizing quantum algorithm in the process of computing, it is expected that this algorithm can solved the problems of image processing faster than using a classical algorithm. In this paper, a quantum digital image halftoning algorithm will be presented.The image would be processed using bitmap image (.bmp) and the applications would be created using Matlab R2009a. Test phase of the applications is using an image, lena.bmp. This application will show three new images as results of three halftoning methods: binary threshold method, ordered dithering method, and method with quantum algorithm. The method with quantum algorithm shows better than two others methods. Kata Kunci: image Processing, quantum Algoritm, halftoning method.

DOI
10.13140/rg.2.1.4661.0965

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Developing new computing methods and signal processing algorithms by borrowing from the principle of quantum mechanics is a very interesting and new research topic. By utilizing quantum algorithm in the process of computing, it is expected that this algorithm can solved the problems of image processing faster than using a classical algorithm. In this paper, a quantum digital image halftoning algorithm will be presented.The image would be processed using bitmap image (.bmp) and the applications would be created using Matlab R2009a. Test phase of the applications is using an image, lena.bmp. This application will show three new images as results of three halftoning methods: binary threshold method, ordered dithering method, and method with quantum algorithm. The method with quantum algorithm shows better than two others methods. Kata Kunci: image Processing, quantum Algoritm, halftoning method.
This article explores and develops a method for the functioning of quantum algorithms and models of quantum computing devices to transform a classical image into a quantum state, highlight boundaries and convert a halftone image into a binary one. The presented quantum algorithm demonstrates the prospects for applying quantum information theory to solve classical problems. The main emphasis of the work is on computer simulation of a quantum algorithm and the study of its effectiveness when using quantum computing tools and methods. The relevance of this research stems from the constant updating and expansion of the field of quantum research, as well as from the lack of computer simulations of quantum physical phenomena. The scientific novelty of the work lies in the development of an effective pattern recognition model using the properties and methods of quantum computing, which contributes to the development of this area of scientific research.
Abstract The aim of the research is computer simulation of a quantum algorithm to solve the problem of transforming a classical image using quantum computing tools and methods, studying recognition algorithms and creating a recognition model using quantum methods. The method of quantum modeling makes it possible to convert a classical image into a quantum state, select boundaries and convert a grayscale image to a binary one, and shows the possibilities of the quantum information theory in interpreting classical problems. The main results of the article are the developed quantum algorithm that allows recognizing objects, as well as the quantum method aimed at representing/processing a color pixel image. The scientific novelty of the article is expressed in the construction of a quantum system, an exponential increase in the speed of solving computational NP-complete problems, which on classical machines can be solved in unacceptable time. The motivation for writing the work was a high growth interest in quantum computing and the benefits that they guarantee. The development of the theoretical foundations of creating software systems and the design of algorithms for new information technologies and specialized computing systems is a dynamic field, as evidenced by the number of existing works in this direction. The developed algorithms for various problems of complexity classes can give a significant gain in efficiency in comparison with existing classical ones and provide a solution to a number of complex mathematical (including cryptographic) problems.
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.
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.
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.
Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms are applied to binary, grey and color images for the first time. Without considering the image preparation, the proposed algorithms achieve exponential acceleration than the existing quantum and classical methods in all three cases. At the end of this paper, an experiment based on the real quantum computer of IBMQ and simulations verify the effectiveness of the algorithms.