Research On Image Processing Algorithm Based On Quantum-derivation

Image is one of the main source for people to obtain and exchange information,and image processing involves all aspects of our lives.Although the application of traditional information processing technology in digital image processing has achieved good results,there are some drawbacks.The development of quantum information technology in recent years,provides a new method for solving problems in digital image processing.Quantum-inspired method is a branch of quantum information technology,it doesn't rely on physical quantum devices,but to improve existing classical signal algorithms or create new ones in electronic computers based on the quantum mechanics basic principles and mathematical theory.With the development of quantum-inspired technology,various image processing algorithms based on quantum-inspired appear and develop rapidly.On this basis,this paper studies three key image processing techniques including image enhancement,image denoising and image edge detection based on quantum-inspired.The main researches include:(1)A wavelet domain image enhancement algorithm based on quantum-inspired is proposed.Firstly,an improved quantum-inspired enhancement operator is given and introduced to enhance approximate information in reconstructed low-frequency image combining the low-frequency and high-frequency coefficient characteristics of wavelet transform.Then Pal-King blur enhancement algorithm is used to enhance detail information of reconstructed high-frequency image.Finally,the enhanced low-frequency reconstructed image and the high-frequency reconstructed image are linearly superimposed to further enhance the image edge and texture information,and the image is enhanced with overall contrast and detail information.The experimental results show that the image enhanced by the proposed algorithm has moderate contrast and brightness,and the image information entropy,image quality measurement function and image sharpness are better than other algorithms.(2)An improved quantum-inspired adaptive median filtering algorithm is proposed.Firstly,image quantization is performed by the quantum bit representation formula of the gray image.Then based on the quantum Hadamard transform and quantum measurement principle,the adaptive median filter template can be constructed through combining the conditional median filtering.Improved algorithm can be adaptive to adjust filter template size and the number of pixels participating in the median operationin the template.The experimental results show that the proposed algorithm has better denoising ability than other comparison algorithms.(3)An image edge detection algorithm based on quantum-inspired is proposed.Firstly,the improved quantum-inspired adaptive median filtering method is used for image filtering and denoising.Then the edge detection template is built through the improved quantum-inspired edge detection operator construction rule and the edge gray image is obtained.Finally,use the non-maximum suppression idea and single threshold to obtain binarized edge image.The experimental results show that compared with other comparison algorithms,proposed algorithm can detect not only the edge of fine and complex structure in image but the edge of image contaminated by salt and pepper noise.