Multi-focus image fusion based on non-subsampled shearlet transform

In this study, a new multi-focus image fusion algorithm based on the non-subsampled shearlet transform (NSST) is presented. First, an initial fused image is acquired by using a conventional multi-resolution image fusion method. The pixels of those source multi-focus images, which have smaller square error with the corresponding pixels of the initial fused image, are considered in the focused regions. Based on this principle, the focused regions are determined, and the morphological opening and closing are employed for post-processing. Then the focused regions and the focused border regions in each source image are identified and used to guide the fusion process in NSST domain. Finally, the fused image is obtained using the inverse NSST. Experimental results show that this proposed method can not only extract more important detailed information from source images, but also avoid the introduction of artificial information effectively. It significantly outperforms the discrete wavelet transform (DWT)-based fusion method, the non-subsampled contourlet-transformbased fusion method and the NSST-based fusion method (see Miao et al. 2011) in terms of both visual quality and objective evaluation.