Quantum computing is a new computing mode that uses quantum superposition,entanglement and coherence properties for efficient quantum parallel computing.Quantum image processing is an emerging field of quantum information science that can enhance the storage,processing,and retrieval of visual information from images and videos by transitioning from digital to quantum modes,or by complementing digital imaging with quantum technologies.ability.The purpose of this paper is to study the quantum implementation of the overall process of the image binary morphological edge detection algorithm.Combined with the IBM Q platform to design the corresponding quantum circuit of the algorithm and realize the quantum simulation of the designed algorithm,the main research work is as follows:(1)Design on quantum image binarization algorithm based on IBM QIn the research of quantum image processing,the research on binary images occupies a considerable proportion,so quantum image binarization algorithm plays a pivotal role in quantum image processing as a quantum image preprocessing algorithm.Aiming at the problem that there is little research on quantum image binarization algorithm,this paper proposes a quantum image binarization algorithm based on IBM Q platform,which is easy to implement and has a simple circuit.First,the optimized extension expresses the NEQR quantum grayscale image representation method;secondly,for the existing ripple-carrying quantum comparators,an adaptive optimized representation of the basic ripple-carrying gate is carried out on the IBM Q platform,and the optimized ripple-carrying gate is used.Gate designed a corresponding quantum circuit for grayscale image binarization;finally completed the IBM Q platform simulation implementation,experimental results and complexity analysis of the quantum image binarization circuit,and compared with the existing quantum image binarization Algorithms are compared in detail,and the correctness and effectiveness of the proposed quantum image binarization algorithm are demonstrated from the perspective of theory and experiment.(2)Design on edge detection algorithm of quantum image binary morphology based on IBM QThere are many researches on quantum image edge detection algorithms,but most of the researches on quantum image edge detection algorithms have the problems that quantum circuit design requires a large number of auxiliary qubits,and the algorithm circuit is complicated,which is difficult to realize in real quantum system simulation.Therefore,this paper proposes a step-by-step implementation of a quantum image binary morphological edge detection algorithm based on the IBM Q platform.First,the NEQR quantum binary image representation method is optimized and improved,so that it can represent the pixel information of the quantum image neighborhood;secondly,based on the quantum binary erosion and expansion operations,the quantum binary morphology denoising and quantum binary Value morphological edge extraction is two easy-toimplement quantum circuits.The quantum image binary morphological edge detection algorithm proposed in this paper is composed of these two quantum circuits.Finally,the quantum image binary morphological edge detection algorithm is given in IBM Q The simulation implementation and experimental results in the platform are also analyzed for complexity,and the effectiveness of the proposed quantum image binary morphological edge detection algorithm is fully demonstrated,and the edge detection effect of the algorithm is verified. |