Research On Quantum Image Enhancement And Circuit Design

Quantum image processing is the application of quantum computing to image processing.Based on the superposition,entanglement,and parallelism of quantum computing,researchers have proposed a variety of quantum versions based on the principles of classic image algorithms.Although scholars at home and abroad have carried out active research on quantum image processing in recent years,its research system is still incomplete and needs further research and improvement.This paper aims to further research the quantum image enhancement algorithm and design the corresponding quantum circuit based on the current mature NEQR representation model.The main research work is as follows:(1)Based on the gray-scale transformation principle of classic images,a piecewise linear transformation circuit of quantum image is designed,which expands the research direction of quantum image enhancement algorithm.Compared with the classical algorithm,the piecewise linear transformation scheme of quantum image designed in this paper reduces the complexity from O(2 ²ⁿ)to O(48q²+62q),achieving exponential acceleration.(2)Aiming at the high complexity of the current quantum median filter and incomplete noise detection,a quantum image approximate median filter algorithm is proposed,and the corresponding quantum implementation circuit is designed.The scheme uses a two-level threshold method to distinguish the signal points and noise points in the image,the gray value of the signal points remains unchanged,and the gray value of the noise points is replaced with the approximate median value of the neighborhood.Compared with the existing algorithms,the approximate median filtering algorithm proposed in this paper better protects the edge and detail information of the image,and reduces the complexity of the quantum circuit by nearly half.(3)A quantum image weighted average filtering circuit is designed.By analyzing the existing quantum image weighted average filtering method,it can be seen that the current method simply migrates the classical algorithm to the quantum without using the characteristics of quantum parallel processing,which leads to the design of the quantum circuit is very complicated and requires a large number of auxiliary bits.In response to the above problems,this paper makes full use of the properties of quantum parallel processing,and proposes an improved quantum image weighted mean filtering scheme.This program first performs a cyclic shift operation on the original image to obtain 9 neighborhood pixel images;then,the 9neighborhood pixel images are multiplied by the corresponding filter coefficients and added to obtain a weighted average filter image,thereby simultaneously realizing the original image filter operation of all pixels.Compared with the existing circuits,the quantum image weighted average filtering circuit designed in this paper has significant advantages in complexity and auxiliary bits.