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Multimodality Image Fusion Based on Quantum Wavelet Transform and Sum-Modified-Laplacian Rule

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Abstract

The parallelism and entanglement characteristics of quantum computation greatly improve the efficiency of image processing tasks. With the sharp increase of data size and requirement of real-time processing in image fusion application, rapid implementation using quantum computation will become the inexorable trend. A novel multimodality image fusion algorithm based on quantum wavelet transform (QWT) and proposed quantum version of sum-modified-laplacian (SML) rule is designed in this paper. The source digital images are firstly represented by flexible representation of quantum image (FRQI) model, and then the quantum form images are transformed with QWT to capture salient features of source images. The quantum version of SML rule is proposed to fuse wavelet coefficients, which has higher efficiency and runs faster than its classical counterpart. The final fused image is obtained by using inverse quantum wavelet transform. The simulations and theoretical analysis verify that the proposed algorithm is effective in the fusion of multimodality images.

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Acknowledgments

The work was funded by the National Natural Science Foundation of China (Grant Nos. 61572089, 61633005, 61802037), the Chongqing Special Postdoctoral Science Foundation (XmT2018032), the Chongqing Research Program of Basic Research and Frontier Technology (Grant No. cstc2017jcyjBX0008) and the Fundamental Research Funds for the Central Universities (Grant Nos. 106112017CDJQJ188830, 106112017CDJXY180005).

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  1. College of Computer Science, Chongqing University, Chongqing, 400044, China

    Xingbin Liu & Di Xiao

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  1. Xingbin Liu
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  2. Di Xiao
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Correspondence to Xingbin Liu.

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Liu, X., Xiao, D. Multimodality Image Fusion Based on Quantum Wavelet Transform and Sum-Modified-Laplacian Rule. Int J Theor Phys 58, 734–744 (2019). https://doi.org/10.1007/s10773-018-3971-4

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