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Image fusion based on simultaneous empirical wavelet transform

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Abstract

In this paper, a new multi-scale image fusion algorithm for multi-sensor images is proposed based on Empirical Wavelet Transform (EWT). Different from traditional wavelet transform, the wavelets of EWT are not fixed, but the ones generated according to the processed signals themselves, which ensures that these wavelets are optimal for processed signals. In order to make EWT can be used in image fusion, Simultaneous Empirical Wavelet Transform (SEWT) for 1D and 2D signals are proposed, by which different signals can be projected into the same wavelet set generated according to all the signals. The fusion algorithm constructed on the 2D SEWT contains three steps: source images are decomposed into a coarse layer and a detail layer first; then, the algorithm fuses detail layers using maximum absolute values, and fuses coarse layers using the maximum global contrast selection; finally, coefficients in all the fused layers are combined to obtain the final fused image using 2D inverse SEWT. Experiments on various images are conducted to examine the performance of the proposed algorithm. The experimental results have shown that the fused images obtained by the proposed algorithm achieve satisfying visual perception; meanwhile, the algorithm is superior to other traditional algorithms in terms of objective measures.

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Acknowledgments

The authors would like to express our gratitude to the editors and anonymous reviewers for their comments and suggestions. The work was supported by Projects in the National Science & Technology Pillar Program, China (2012BAH48F02), National Science Foundation of China (Grant No. 61272209), Technology Development Plan of Jilin Province (201105017), and Agreement of Science & Technology Development Project, Jilin Province (No. 20150101014JC).

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Authors and Affiliations

  1. Key Laboratory of Symbol Computation and Knowledge Engineer of Ministry of Education, Jilin University, Changchun, 130012, China

    Xiaoli Zhang, Xiongfei Li & Yuncong Feng

  2. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Xiaoli Zhang, Xiongfei Li & Yuncong Feng

Authors
  1. Xiaoli Zhang
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  2. Xiongfei Li
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  3. Yuncong Feng
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Correspondence to Xiongfei Li.

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Zhang, X., Li, X. & Feng, Y. Image fusion based on simultaneous empirical wavelet transform. Multimed Tools Appl 76, 8175–8193 (2017). https://doi.org/10.1007/s11042-016-3453-8

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  • DOI: https://doi.org/10.1007/s11042-016-3453-8

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