Background:
A multi-scale multidirectional image fusion method is proposed, which
introduces the Nonsubsampled Directional Filter Bank (NSDFB) into the multi-scale edge-preserving
decomposition based on the fast guided filter.
Methods:
The proposed method has the advantages of preserving edges and extracting directional
information simultaneously. In order to get better-fused sub-bands coefficients, a Convolutional Sparse
Representation (CSR) based approximation sub-bands fusion rule is introduced and a Pulse Coupled
Neural Network (PCNN) based detail sub-bands fusion strategy with New Sum of Modified Laplacian
(NSML) to be the external input is also presented simultaneously.
Results:
Experimental results have demonstrated the superiority of the proposed method over
conventional methods in terms of visual effects and objective evaluations.
Conclusion:
In this paper, combining fast guided filter and nonsubsampled directional filter bank, a
multi-scale directional edge-preserving filter image fusion method is proposed. The proposed method
has the features of edge-preserving and extracting directional information.
Multi-scale image fusion for x-ray grating-based mammography