关键词: 多聚焦图像融合, 经验小波变换, 可协调, 改进Laplacian能量和, Log-Gabor能量

Abstract: This paper applies the Empirical Wavelet Transform（EWT） on multi-focus image fusion. EWT is an adaptive signal decomposition method. It has a better performance than empirical mode decomposition and traditional wavelet decomposition in some extent. The key ideal of EWT is realizing the signal decomposition by constructing an adaptive filter bank. However, performing EWT decomposition to each of the two multi-focus images independently may generate two different filter banks and result in mismatch between two corresponding sub-bands to be fused, which will affect the quality of the result image. To solve this problem, a Coordinative Empirical Wavelet Transform（C-EWT） is proposed. Under the C-EWT decomposition, each corresponding sub-band of the two multi-focus images is matched. Furthermore, a new image fusion algorithm based on C-EWT is proposed. The fusion procession is as follows.Firstly, two source images are decomposed into a low frequency sub-band and some high frequency sub-bands, respectively. Then, the low-frequency sub-bands are fused with the fusion rule based on the sum-modified-Laplacian, while the corresponding high-frequency sub-bands are fused with the fusion rule based on the local Log-Gabor energy. Finally, the fused sub-images are combined to reconstruct the fused image. Experiments on four sets of images are conducted to compare the proposed algorithm with other six algorithms. The experimental results have shown that the proposed algorithm has advantages in integrating focus areas, preserving edges and details. Meanwhile, the fusion result by the proposed algorithm has more satisfying visual effect and its objective evaluation index is the closest to the standard fusion image.

Key words: multi-focus image fusion, empirical wavelet transform, coordinate, sum-modified-Laplacian, Log-Gabor energy