Research On Quantum Image Denoising Algorithm Based On Wavelet Transform

Image denoising is an important part of image processing technology.In recent years,with the rapid development of science and technology,a large number of digital images emerge as the times.However,in the process of acquiring digital images,they are often disturbed by external factors,such as equipment,environment and so on.Inevitably,they are polluted by noise,which directly affects a series of subsequent applications.Therefore,image denoising plays an important role in image processing and is still an important research topic.A quantum denoising algorithm based on dual-tree and dual-density complex wavelet transform is proposed.The innovation of the algorithm is mainly embodied in two aspects: on the one hand,the image information is described in more detail through the combination of quantum image coding and wavelet transform;on the other hand,the quantum denoising factor is deduced and improved to effectively distinguish the image edge information from the noise part.The research work in this paper is as follows:(1)Researches are conducted on the main types and causes of noise in the image,as well as the advantages and shortcomings of traditional image processing algorithms.The basic principles and implementation processes of one-dimensional and two-dimensional wavelet transform,dual-tree complex wavelet transform,dual-density dual-tree complex wavelet transform and dual-density dual-tree complex wavelet transform are studied.The characteristics and advantages of various wavelet transforms are analyzed in detail,and the advantages are combined to provide a theoretical basis for the later quantum denoising algorithm.(2)The formation and development of the theory of quantum image processing are introduced,and also the expression with processing methods of quantum image and the quantum expression and processing of image is studied in this paper.The concepts and ideas of quantum theory are extended to the field of image processing,and the expression of quantum image is explored.The idea of quantum superposition state is introduced into the field of image processing to improve the filtering effect of algorithm on salt and pepper noise and Gauss noise.The experimental results show that the double-density dual-tree complex wavelet quantum denoising algorithm has good filtering effect on both salt and pepper noise and Gaussian noise,and processing speed is relatively fast,which was significant for quantum theory develops new research direction in image processing field.(3)This paper mainly studies quantum denoising factor(DF),introduces quantum theory,improves dual-density dual-tree complex wavelet transform,and forms quantum denoising algorithm.The algorithm firstly performs logarithmic transformation and double-density dual-tree complex wavelet transform on the noise-added images to obtain wavelet coefficient,after which is normalized,use the maximum posterior probability estimator(MAP)in Bayesian theory to estimate the variance of image information and noise.Subsequently,processing continuously noised wavelet coefficient in layers by modifying quantum deoising factors parameter to obtain denoised wavelet coefficient.And finally the denoised image can be got after exponential transform by the wavelet reconstruction Mallet algorithm.The experimental results demonstrate the effectiveness and innovation of the algorithm,which can design and implement a software system for quantum image processing.