Nonsubsampled Shearlet Transform Domain Research Articles

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.

Technique for image fusion based on NSST domain improved fast non-classical RF

In this paper, a novel technique for image fusion based on NSST (Non-Subsampled Shearlet Transform) domain improved fast non-classical RF (Receptive Field) is proposed to resolve the problem of the multi-sensor image fusion. As a novel multi-scale geometric analysis tool, NSST can be optimally efficient in representing images containing edges and capturing the geometric features of multidimensional data. As a result, NSST is introduced into the field of image fusion in this paper and utilized to obtain the final fused image. Multi-scale and multi-directional sparse decompositions of source images are performed by NSST to obtain the main and detailed information. Then, the basic traditional RF model is modified to be an improved fast non-classical RF (IFRF) which has much fewer parameters and a more effective structure compared with RF. Thirdly, with IFRF and the model of local directional contrast (LDC), the fused sub-images can be achieved. Meanwhile, the algorithm for image fusion based on NSST domain improved fast non-classical RF is devised. Finally, the final fused image can be obtained by using inverse NSST to all fused sub-images. The numerical experiments demonstrate that the new technique presented in this paper has not only much better performance, but good running efficiency.