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量子計算に基づく画像データ探索、電子透かし及び感情空間の表現法

YAN, FEI, YAN, FEI

Published Mar 1, 2014• 0 citations
OpenAlex

Abstract

Quantum computation is a promising and rapidly growing field that has witnessed a series of significant breakthroughs in the last several decades.While some practitioners envision the realization of complete quantum computing devices, the research presented in the thesis focusses on the works that we can do with quantum computing hardware when they are realized.One of such areas is that of quantum image processing.A Flexible Representation of Quantum Images (FRQI) allows us to dedicate n-qubits and 1-qubit to capturing the information about the position and color of every pixel in the image, respectively.A method to compare multiple pairs of quantum images in parallel is proposed, where the similarities of the images are estimated according to the probability distributions of the readouts from quantum measurements.It offers a significant speed-up in comparison to performing the same task on traditional computing devices by means of a single Hadamard gate with control-conditions to transform the entire information encoding the quantum images in a strip.The simulation experiments comprising of the comparison of two images, multiple pairs of images, and the sub-blocks from two images are implemented to demonstrate the feasibility and efficiency of the parallel comparison.On the basis of such a comparison strategy, a quantum image searching method is presented where the image in a 4 × 4 binary image database with the highest similarity value to the particular test image is retrieved as the search result using low computational resources.To process the RGB-like quantum image, the representation for Multi-Channel Quantum Images (MCQI) is given, and a double-key, double-domain watermarking strategy for i

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Quantum computation is a promising and rapidly growing field that has witnessed a series of significant breakthroughs in the last several decades.While some practitioners envision the realization of complete quantum computing devices, the research presented in the thesis focusses on the works that we can do with quantum computing hardware when they are realized.One of such areas is that of quantum image processing.A Flexible Representation of Quantum Images (FRQI) allows us to dedicate n-qubits and 1-qubit to capturing the information about the position and color of every pixel in the image, respectively.A method to compare multiple pairs of quantum images in parallel is proposed, where the similarities of the images are estimated according to the probability distributions of the readouts from quantum measurements.It offers a significant speed-up in comparison to performing the same task on traditional computing devices by means of a single Hadamard gate with control-conditions to transform the entire information encoding the quantum images in a strip.The simulation experiments comprising of the comparison of two images, multiple pairs of images, and the sub-blocks from two images are implemented to demonstrate the feasibility and efficiency of the parallel comparison.On the basis of such a comparison strategy, a quantum image searching method is presented where the image in a 4 × 4 binary image database with the highest similarity value to the particular test image is retrieved as the search result using low computational resources.To process the RGB-like quantum image, the representation for Multi-Channel Quantum Images (MCQI) is given, and a double-key, double-domain watermarking strategy for i
A method to compare multiple pairs of quantum images in parallel is proposed, where the similarities of the images are estimated according to the probability distributions of the readouts from quantum measurements. The proposed method by means of a single Hadamard gate with control-conditions to transform the entire information encoding the quantum images in a strip, offers a significant speed-up in comparison to performing the same task on traditional computing devices. Three simulation experiments comprising of the comparison of two images, multiple pairs of images, and the sub-blocks from two images are implemented using MATLAB to demonstrate the feasibility and efficiency of the parallel comparison. The proposal advances a fundamental step towards image searching on quantum computers in which the image with the highest similarity to a particular reference image is retrieved as a search result from a database.
Quantum image processing is a new and exciting subdiscipline of quantum computation that aims to extend classical image processing applications on a quantum computer.The research starts with a proposal of a representation of images on a quantum computer, named Multi-Channel Representation for Quantum Images (MCQI).This representation encodes the positions and their corresponding colors in the images as a normalized quantum state.For an n by n sized image, 2n qubits and 3 qubits are used to carry the position and color respectively.The preparation procedure of a quantum image is discussed by the multi-channel polynomial preparation, which turns the initial quantum states to the MC-QI quantum states.The image retrieval procedure by quantum measurement is proposed which converts the quantum states to classical images.Furthermore, based on MCQI, some categories of possible processing transformations are suggested.By considering the structure of MCQI representation, the Channel of Interest (CoI), the Channel Swapping (CS), the Color Space Transformation (CST), and Alpha Blending (αB) quantum image processing operators are discussed using unitary transformations with low complexity.All the 4 operators are used to process the information about color in the images.Their complexity are analyzed in terms of the number of basic quantum gates which are needed to build the transformations, and they can be built by 9, 3, 287, 28 basic quantum gates, respectively.Some strategies for designing new transformations from known ones are proposed as well.These strategies can be used to design further algorithms for image processing.Based on the MCQI representation and the four image processing operators, a quantum measurement based double-key double-domain watermarking strategy for multichannel quantum images (MC-WaQI) is developed.In these application, a revised of the original MCQI representation and some restricted versions of the transformations are considered.The research provides the foundation to design other quantum image processing algorithms and can be extend to the following areas:• MCQI representation can be used to build quantum image database,• new frequency operations on quantum images based on quantum Fourier quantum discrete cosine, and quantum wavelet transformations,• building the special effect on color quantum movie,• image data transmission by quantum communication.
A flexible representation of quantum images (FRQI) was proposed to facilitate the extension of classical (non-quantum)-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI) and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI), quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.
A quantum image searching method is proposed based on the probability distributions of the readouts from the quantum measurements. It is achieved by using low computational resources which are only a single Hadamard gate combined with m + 1 quantum measurement operations. To validate the proposed method, a simulation experiment is used where the image with the highest similarity value of 0.93 to the particular test image is retrieved as the search result from 4 × 4 binary image database. The proposal provides a basic step for designing a search engine on quantum computing devices where the image in the database is retrieved based on its similarity to the test image.
RGB multi channel representation is proposed for images on quantum computers (MCQI) that captures information about colors (RGB channels) and their corresponding positions in an image in a normalized quantum state. The proposed representation makes it possible to store the RGB information about an image simultaneously by using 2n+3 qubits for encoding 2n× 2npixel images, whereas pixel-wise processing is necessary in many other quantum image representations, e.g., qubit lattice, grid qubit, and quantum lattice. Simulation of storage and retrieval of MCQI images using human facial images demonstrated that 15 qubits are required for encoding 64 × 64 colored images, and encoded information is retrieved by measurement. Perspectives of designing quantum image operators are also discussed based onMCQI representation, e.g., channel of interest, channel swapping, and restrict version of color transformation.
Flexible Representation of Quantum Images (FRQI) is proposed to provide a representation of images that enables efficient preparation and image processing operators on quantum computers. FRQI captures colors and their corresponding positions in an image into a quantum state. The preparation with polynomial simple operations for FRQI turning a quantum computer from the initialized state to the FRQI state is done by using Hadamard and controlled rotation gates. The Quantum Image Compression (QIC) algorithm reduces simple operations used in the preparation process based on the minimization of Boolean equations are from same color groups of positions. Quantum image processing operators on FRQI based unitary transforms dealing with only colors, colors at some positions and the combination by the quantum Fourier transform of both colors and positions are addressed. The experiments for the storage and retrieval of images using FRQI are implemented in Matlab. The compression ratio of QIC among same color groups ranges from 6.67% to 31.62% on the Lena image.