Research On Quantum Image Scale And Watermarking Technology

Quantum computing due to its reversibility,no energy dissipation etc.,making the development of quantum computer has become a historical necessity.Due to the unique advantages of quantum computing,such as superposition,entanglement and coherence,quantum computation can greatly improve the efficiency of complex image processing.As a newly emerging interdiscipline,quantum image processing has become a hot research topic in the field of quantum computing,quantum information and image processing.Quantum image processing aims to extend the task and operation of classical image processing into the quantum processing framework,including capturing,manipulating and restoring quantum images.To realize the task of image processing on a quantum computer,it is mainly divided into the following two aspects: First,the image representation mode is defined on a quantum computer;second,a quantum image processing algorithm is designed.The main work of this paper is based on the mature quantum image representation models,further develop the quantum image processing algorithms and design the corresponding quantum circuits,the main contents are as follows:(1)Research on bilinear interpolation technique for quantum grayscale imageQuantum image scaling,both the image enlargement and reduction,inevitably uses interpolation algorithms to determine the pixels value in resulting images.Based on the previous researches both at home and abroad,nearest-neighbor interpolation algorithm has been widely used in the scaling of quantum images.However,there is a clear zigzag phenomenon in the quantum image based on the nearest neighbor interpolation and scaling,so it is necessary to further propose an interpolation algorithm with better effects.Based on the bilinear interpolation principle of classical images,the third chapter proposes a quantum image scaling algorithm based on bilinear interpolation.Firstly,the rationality of quantum grayscale image scaling using bilinear interpolation is analyzed and verified.Then,a complete bilinear interpolation circuit is given based on the quantum gray image represented by NEQR.Finally,the complexity analysis and experimental simulation results of the quantum grayscale image scaling circuit are given.(2)Research on bilinear interpolation technique for quantum color imageBased on the three-channel representation of quantum RGB color images and the bilinear interpolation algorithm,Chapter 4 of this paper proposes a bilinear interpolation scaling scheme for quantum color images.Firstly,a series of quantum circuit modules with specific functions is designed,which will be further used for bilinear interpolation of quantum color image.Secondly,analyze and verify the rationality and feasibility of the bilinear interpolation principle in quantum RGB color image scaling.Finally,the circuit for quantum color image scaling using bilinear interpolation is constructed,and the complexity analysis of quantum scaling circuit and experimental simulation results are given.(3)Research on quantum grayscale image watermarking based on least significant bit and Arnold transformSimilar to the information hiding of classical images,quantum image information hiding also includes encryption and watermark.Based on classical Arnold image scrambling and least significant bit LSB scheme,quantum image information hiding has been widely developed.Based on the basic work of researchers both at home and abroad,the fifth chapter presents quantum grayscale image watermarking scheme based on Arnold transform and the least significant bit encryption.Among them,the mode N plus quantum circuit module implements Arnold forward scrambling operation,and the mode N minus quantum circuit implements reverse Arnold inverse scrambling operation.When embedding and extracting the pixel information at the same position coordinate,the quantum equal circuit is designed to compare whether the coordinate position information between the two images and the multiple images are the same or not.Finally,a complete circuit for embedding and extracting quantum watermarking images is given,and the computational complexity analysis of quantum circuits and experimental simulation results are given.(4)Research on quantum color image watermarking based on least significant bit and Arnold transformBased on the Arnold transform's double-scramble algorithm of position space and pixel grayscale space and LSB steganography,a quantum color image watermarking scheme is proposed in sixth chapter.Wherein,the embedding of the watermark image is mainly:(1)The dual scrambling algorithm using Arnold transform obtains a watermark image without meaning after scrambling;(2)further expanding the Arnold transform double-scrambled quantum color watermark image to get a watermark image of which size is same as the quantum color carrier image.(3)implementing the steganography LSB embeds the quantum color watermark image,and at the same time,a key image of the same size as the carrier image is generated.The extraction process of the watermark image is a completely opposite operation process from the embedding process.Based on the embedding and extraction process of the watermark image,we provide a complete quantum circuit design.Based on the analysis of the computational complexity of quantum circuits,it can be concluded that the proposed quantum color watermarking scheme has a lower computational complexity.Experimental results analysis the proposed color watermarking scheme has better concealment and robustness.