Quantum Pseudo-color Processing And Its Application In Weld Image Processind

Pseudo-color processing refers to the processing of assigning color value to gray value according to certain criteria,which can improve the detail resolution ability of human eyes on the image.Pseudo-color processing is a common method used for image enhancement.Quantum image processing is based on quantum mechanics and has parallel computing ability,which has certain advantages in solving complex image processing tasks.Quantum pseudo-color processing is based on the theory of quantum image processing and has some advantages in computing speed.In this paper,pseudo-color processing algorithm of quantum image is studied,and its application in image processing of weld seam is explored.Its main work is summarized as follows:（1）Firstly,in order to solve the storage problem of images represented by RGB color model in quantum computer,two new quantum image representation models are proposed in this paper,namely the General Quantum Image Representation with Multi-color Channels（GQIRMC）model and the New Enhanced Quantum Image Representation with Multi-color Channels（NEQRMC）model.GQIRMC model is based on the General Quantum Image Representation（GQIR）model.The improved model can represent high-dimensional color images whose horizontal and vertical coordinates are any positive integers.Compared with the GQIR model,the spatial complexity of the GQIRMC model is reduced to[log₂ M]+[log₂S]+q+2 when representing RGB color images of size M × S。The NEQRMC model is an improved model based on the New Enhanced Quantum Image Representation（NEQR）model.Compared with the NEQR model,[log₂D]qubits are added to represent the channel information of color dimension,which can represent RGB color images with size of 2n × 2n and space complexity of 2n+q+2.（2）Secondly,based on GQIR model and GQIRMC model,two new quantum image pseudo-color processing algorithms are proposed.They are quantum image density stratification method and quantum image gray level-color transformation method.According to the characteristics of the algorithm,the quantum circuit of the algorithm is designed and completed.The quantum image density stratification method uses the quantum color mapping table to complete the mapping work from gray value to RGB color value,which can deal with the arbitrary division of gray value interval in the quantum color mapping table.The key to realize the quantum circuit is the design of the quantum threshold circuit,which mainly uses the controlled quantum gate to realize the algorithm function.The algorithm has a spatial complexity of O（m+s+p+t）and a time complexity of O（t[m+s+p）).2m×2s is the size of the image,P is the color depth of the image,and t is the number of intervals divided by the color mapping table.The quantum image gray grade-color transformation method realizes color mapping based on the hot metal coding function.The quantum circuit to realize the mapping can be divided into three parts:R channel converter,G channel converter and B channel converter.The spatial complexity of the algorithm is O（m+s+p）,and the time complexity is 2947.（3）Finally,the two quantum pseudo-color processing algorithms proposed in this paper are applied to the processing of weld images to enhance the detail of the defects and improve the clarity of the images.Due to the problems of high noise and low contrast of weld images obtained by X-ray,the original film was preprocessed,including noise reduction and gray equalization.Then,based on GQIR model,the quantum representation of the preprocessed weld image was constructed.The quantum weld image is processed with quantum image pseudo color,and then quantum measurement is carried out to obtain the classical pseudo color weld image.The simulation results show that the two algorithms can improve the efficiency of image processing.Based on the superposition and entanglement of quantum states,the efficiency of the two quantum image pseudo-color processing algorithms proposed in this paper is exponentially higher than that of the classical algorithms.Moreover,the algorithm is applied to the defect detection of weld image,and the image enhancement processing of weld film is realized,which solves the problem that the X-ray weld film is not clear which leads to the disadvantage of defect determination.