Research On Pseudo-color Enhancement Algorithm For Quantum Image

At present,image representation and image processing algorithms in quantum computers have attracted the attention of scholars.As a branch of classical image enhancement,pseudo-color enhancement transforms each gray value of the image into different color values according to the mapping criteria.It can improve the resolution of the image and effectively enhance the ability of the human eye to recognize the details of the original image,which is more conducive to the acquisition of image information.Quantum image pseudo-color enhancement is a branch of quantum image processing algorithms.Using the parallelism and entanglement of quantum computing,it can efficiently complete the processing tasks of large batches of image data,which has great advantages in processing speed and accuracy.Therefore,the study of quantum image pseudo-color enhancement algorithm has a certain role in promoting the development of current artificial intelligence technology and the theoretical perfection of future quantum computers.This paper mainly studies the quantum image pseudo-color enhancement algorithm and its optimal design of quantum circuits,and applies the research results to the processing of medical and weld images.The specific research contents are described as follows:(1)According to the principle of classical density layering method,a pseudo-color enhancement algorithm of quantum image bit plane is proposed,and corresponding quantum circuits are designed with NEQR and QRCI as the input and output quantum image representation models respectively.The gray value of the image is mapped to the color value mainly through two quantum threshold circuits and a gray value mapping table suitable for the quantum computing environment.When the algorithm processes an image with a size of 2~n?2~n and a color depth of2~q,if the mapping table interval is specifically divided into t segments,the time complexity is O(t)and the space complexity is O(2n+q+7);If the mapping table interval is arbitrarily divided into t segments,the time complexity remains unchanged,and the space complexity is O(2n+2q+10).Compared with the classical algorithm and the existing quantum version algorithm,the space overhead is significantly reduced.(2)According to the principle of the classical grayscale-color transformation method,a rainbow-encoded pseudo-color enhancement algorithm for quantum images is proposed,and corresponding quantum circuits are designed with NEQR and QRMW as the input and output quantum image representation models respectively.When the algorithm processes an image with a size of 2~n?2~n and a color depth of 2~q,the number of quantum fundamental gates required is 3253,the time complexity is only constant O(1),and the space complexity is O(2n+2q+2).Then,the quantum circuit is compressed based on its own temporary spare qubits,the number of quantum fundamental gates after compression is reduced to 2244,the quantum cost is reduced by 31.02%,and the space complexity remains unchanged.Finally,an auxiliary qubit is added to the compressed quantum circuit to temporarily store the result of n-CNOT gate decomposition,which further optimizes the quantum circuit.After optimization,the number of quantum fundamental gates is reduced to 958,the quantum cost is reduced by 70.55%,and the space complexity is O(2n+2q+3).Compared with the classical algorithm and the existing quantum version algorithm,the space overhead and quantum cost are significantly reduced.(3)Simulation experiments are carried out under the IBM Qiskit quantum computing framework,and the proposed quantum image pseudo-color enhancement algorithm is applied to the processing of medical and weld images.The information entropy and sharpness indicators of the processed images are good,and the experimental results prove the feasibility of the proposed algorithm.