Quantum multidimensional color images similarity comparison

Hai-Sheng Li, Qingxin Zhu, Ri‐Gui Zhou +3 more

Ping Fan, Ri‐Gui Zhou, Naihuan Jing +1 more

Ri‐Gui Zhou, Canyun Tan, Ping Fan

Reviewing past researches on quantum image scaling, only 2D images are studied. And, in a quantum system, the processing speed increases exponentially since parallel computation can be realized with superposition state when compared with classical computer. Consequently, this paper proposes quantum multidimensional color image scaling based on nearest-neighbor interpolation for the first time. Firstly, flexible representation of quantum images (FRQI) is extended to multidimensional color model. Meantime, the nearest-neighbor interpolation is extended to multidimensional color image and cycle translation operation is designed to perform scaling up operation. Then, the circuits are designed for quantum multidimensional color image scaling, including scaling up and scaling down, based on the extension of FRQI. In addition, complexity analysis shows that the circuits in the paper have lower complexity. Examples and simulation experiments are given to elaborate the procedure of quantum multidimensional scaling.

Ri‐Gui Zhou, XingAo Liu, Changming Zhu +3 more

XingAo Liu, Ri‐Gui Zhou, Ahmed El-Rafei +2 more

Y. Liu, Zai-dong Qi, Qiang Liu

Comparing the similarity between digital images is an important subroutine in various image processing algorithms. In this study, we present three quantum algorithms for comparing the similarity between two quantum images. These algorithms are applied to binary, grey and color images for the first time. Without considering the image preparation, the proposed algorithms achieve exponential acceleration than the existing quantum and classical methods in all three cases. At the end of this paper, an experiment based on the real quantum computer of IBMQ and simulations verify the effectiveness of the algorithms.