Abstract:
In order to fuse multiple visible-light images with different focuses efficiently,a multi-focus image fusion method based on structural similarities and local energies in Curvelet domain is proposed. In this method, the original images are first decomposed with Curvelet transform and the coefficients of low-frequency and high-frequency in Curvelet domain are obtained. Then, the low-frequency coefficients are gained by averaging the two groups of low-frequency coefficients, while the high-frequency coefficients are decided by the structural similarity depending on their local energies. Finally,the fused image is reconstructed by inverse Curvelet transform. Experimental results indicate our method not only can efficiently integrate the detail information, but also is superior to some widely-used methods, such as principal component analysis method, Laplacian pyramid method, and wavelet transform based method, when the entropy, standard deviation and clarity of fused images are compared.
