Research On Security And Confidentiality Technology Of HSI Color Space Based Quantum Image

Benefiting from the blazing growth of quantum computing theory and related technologies,the distance between people and quantum computers with parallel computing capabilities is becoming smaller and smaller.On the one hand quantum computers can shoulder the burden of solving the difficult problems of high capacity and ultra-high speed that classical computers cannot solve,but on the other hand quantum computers constitute a fundamental threat to the traditional security field,which appears particularly outstanding in the field of image processing.The existing image confidentiality technology was built within the famework of classical computers,and cannot be directly transplanted to quantum computers.In order to perfect the research contents of quantum image theory and further improve the security of images on quantum computers,investigating the security and confidentiality technology for quantum images has become an imminent problem.The paper opens with a statement of knowledge about quantum image representation,processing and security.This is immediately followed by research on quantum color image elementary operations and encryption algorithms.Since both of these operations(algorithms)are based on the quantum color image representation model,this paper firstly presents a new and innovative quantum color image representation model,secondly designs a new theory of elementary operations for this model,and finally constructs an encryption algorithm from a completely new perspective.The principal research work and innovation results of this paper are summaried as follows.(1)The quantum image representation method QIRHSI(Quantum Image Representation based on the HSI color space)was designed.This model uses two angular vectors to encode Hue(H)and Saturation(S)respectively,and a binary sequence of q qubits to encode Intensity(I),which not only requires less storage space for the H and S channels than the existing quantum color image representation models,but also makes it easier to perform various color processing operations on I channel.In addition,the image preparation resources of the QIRHSI model are optimized using the Boolean expression minimization principle.(2)The quantum arithmetic operations based on QIRHSI representations,including intensity reverse operations,complement operations,addition operations and subtraction operations,are investigated,and the corresponding quantum circuits are designed.By analyzing the complexity of the quantum gates needed for the quantum gates,it can be seen that the designed quantum circuits can efficiently carry out quantum arithmetic operations.(3)The quantum geometric transformations based on the QIRHSI representation,covering two-point swapping,circular translation,flip transformation and right angle rotation,are designed and the corresponding quantum circuits are given respectively.By analyzing the complexity of the basic quantum gates required for each quantum network,the quantum geometric transformation operations can be efficiently implemented.(4)The quantum image scaling transformation of the IQIRHSI(Improved QIRHSI)model based on the nearest neighbour interpolation method is designed to extend the image from size 2ⁿ×2 ⁿ to2ⁿ¹×2 ⁿ²,and algorithms and quantum circuits for the quantum image scaling transformation are designed.By analyzing the complexity of the quantum image scaling circuits,it is possible to implement scale scaling operations on IQIRHSI images.(5)The proposed algorithm is a quantum color image encryption based on geometric transformation and intensity channel diffusion.Combined with the pseudo-random sequence generated by the generalized Logistic map,the pixel positions of the quantum image are made“disordered”by using 2^2n-1 two-point swap operations.Next,the intensity values are changed by intensity bit-plane cross-swap operations and XOR,XNOR-operations.Finally,the pseudo-random sequence produced by the quantum Logistic mapping is used to achieve the diffusion of the intensity components.The algorithm effectively improves the security of the quantum image encryption algorithm.