研究目的
To propose a method that maintains the characteristics of the original BEMD method while reducing computation time and improving fusion quality by using Hermite interpolation reconstruction and variable neighborhood window method.
研究成果
The proposed method achieves fast decomposition, maintains data-driven, self-adaption, and scale consistency, overcomes the shortcomings of the original BEMD method, and reduces computational time and cost, providing a better method for image fusion.
研究不足
The method requires iterative filtering and interpolation, which may still be computationally intensive despite improvements.
1：Experimental Design and Method Selection:
The method involves replacing surface interpolation with Hermite interpolation reconstruction and using a variable neighborhood window method instead of a fixed one.
2：Sample Selection and Data Sources:
Common fusion images are used for analysis.
3：List of Experimental Equipment and Materials:
Not specified.
4：Experimental Procedures and Operational Workflow:
The source image is decomposed using bi-dimensional empirical mode decomposition, and the decomposed image is fused according to the fusion method.
5：Data Analysis Methods:
PSNR and information entropy are introduced to compare the final fusion results of image quality.
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