4.6 Article

Multilevel 2-D Quantum Wavelet Transforms

期刊

IEEE TRANSACTIONS ON CYBERNETICS
卷 52, 期 8, 页码 8467-8480

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2021.3049509

关键词

Transforms; Wavelet transforms; Logic gates; Tensors; Image processing; Wavelet packets; Image color analysis; Multilevel 2-D-Daubechies quantum wavelet transform (QWT); multilevel 2-D-Haar QWT; quantum image processing

资金

  1. National Natural Science Foundation of China [61762012, 62062035, 61763014]
  2. Science and Technology Project of Guangxi [2020GXNSFDA238023, 2018GXNSFAA281155]
  3. Science and Technology Research Project of Jiangxi Provincial Education Department [GJJ190297]

向作者/读者索取更多资源

Researchers have proposed one-dimensional quantum wavelet transforms and generalized them into multilevel and multidimensional, constructing the general theory of multilevel 2-D QWT. They have built the multilevel 2-D Haar QWT and Daubechies D4 QWT, along with providing complete quantum circuits. These transforms offer exponential speedup over their classical counterparts in terms of complexity and speed.
Wavelet transform is being widely used in classical image processing. One-dimension quantum wavelet transforms (QWTs) have been proposed. Generalizations of the 1-D QWT into multilevel and multidimension have been investigated but restricted to the quantum wavelet packet transform (QWPTs), which is the direct product of 1-D QWPTs, and there is no transform between the packets in different dimensions. A 2-D QWT is vital for image processing. We construct the multilevel 2-D QWT's general theory. Explicitly, we built multilevel 2-D Haar QWT and the multilevel Daubechies D4 QWT, respectively. We have given the complete quantum circuits for these wavelet transforms, using both noniterative and iterative methods. Compared to the 1-D QWT and wavelet packet transform, the multilevel 2-D QWT involves the entanglement between components in different degrees. Complexity analysis reveals that the proposed transforms offer exponential speedup over their classical counterparts. Also, the proposed wavelet transforms are used to realize quantum image compression. Simulation results demonstrate that the proposed wavelet transforms are significant and obtain the same results as their classical counterparts with an exponential speedup.

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