The Research Of Quantum Image Processing Algorithm And Simulation

With the advent of many new technologies,the functionality of classical image processing algorithms is becoming increasingly inadequate.Faced with these complex functions,the existing computing technology is inefficient.Because of the unique properties of quantum computing,such as superposition and entanglement,researchers have fused quantum computing with traditional image processing methods,and this method is considered as one of the promising means to solve the limitations of traditional image development.At present,quantum image processing has become a research hotspot,which shows great potential in the huge amount of data stored in the image and the high precision of processing.Quantum image processing includes image representation model,geometric transformation,image segmentation,quantum morphology,edge extraction,image matching,quantum watermarking and so on.This paper mainly studies some quantum image processing algorithms and corresponding circuit design based on classical operators.The main research contents are as follows:1.The segmentation algorithm based on image edge extraction is very important for fast image segmentation.A quantum image edge extraction algorithm based on Kirsch operator is proposed and studied.In the algorithm,the new enhanced quantum image representation model is used as the image storage model of quantum image processing,and Kirsch operator is used to generate edge extraction results.Because the neighborhood detection results of each pixel of Kirsch operator are independent of other pixels,Kirsch operator can be used for real-time detection in the case of parallel computation.According to mean square error and peak signal-to-noise ratio,we analyzed the image quality of the quantum edge extraction algorithm after edge extraction,which can reach up to 41.5312d B,which shows a good image quality.We carry out the design,analyses,and simulations of quantum circuits based on our approach,which shows that the image processing speed and accuracy are much better than the classical edge extraction algorithms.2.Image restoration algorithm is still one of the focuses in the field of graphics processing.Many achievements have been made in the representation and processing of images by quantum technology,but not in the restoration of quantum images.Therefore,a constrained least square filter based on quantum image restoration model is proposed and studied.In this model,a priori knowledge is employed to reconstruct or estimate the point spread function(PSF),and a non-degenerate estimate is obtained according to the opposite process.The sensitivity of fuzzy function to noise is solved based on the optimal measure of smoothness.Under the constraint condition,we expect to determine the minimum criterion function to estimate the original image function.For some motion blur and various noise pollution,the algorithm can perform better.In our method,we design the quantum circuit based on Laplacian operator,and the model can still show strong robustness in low intensity noise attack.For 2~"2~" an image,we implement a quantum circuit based on Laplace operator,which can solve the problem of image blurring.The simulation results show that this algorithm has a good image restoration effect.For the quantum image model,we can construct the quantum circuit under the computational complexity and carry on the image deblurring processing.3.For the real-time and high-precision image processing,even powerful classical computers and complex algorithms cannot be very satisfactory.Therefore,quantum Richardson-Lucy algorithm is proposed on controlled rotation operation and Hamiltonian evolution is proposed and studied.A flexible representation of quantum image is introduced as an image representation mode and amplitude variation is controlled by a controlled revolving door.After the controlled rotation operation,the quantum states on the quantum registers are required to quantify the Richardson-Lucy model through the Hamiltonian evolutionary construction of the quantum gate.Finally,the quantum gate constructed by non-sparse Hamiltonian evolution technique is used to further operate the quantum state after controlled rotation,and all quantum states of stored pixel information are reduced to clear the quantum image.The algorithm has good image quality under the condition of oscillation blur and Gaussian noise.