Panchromatic and multi-spectral image fusion method based on two-step sparse representation and wavelet transform

Based on the characteristics of two-step sparse coding and multi-scale analysis of wavelet transform, a novel fusion algorithm based on two-step sparse coding (Two Step Sparse Representation, TSSR) and wavelet transform is proposed. The two-step sparse strategy is used to construct the corresponding dictionary for the low-frequency component and the down- sampled low-frequency component respectively, which avoids the training process of the traditional sparse representation and improves the computing speed. At the same time, the sparse coefficient solution based on two-step sparse coding is closer to the original signal than the one-step sparse solution in traditional sparse representation, and the precision of the algorithm is higher. Experimental results and analysis show that the proposed method can not only keep the spectral characteristics, but also can effectively integrate the spatial detail information of panchromatic images. The computing time is much faster than the traditional sparse method, and it has more advantages than wavelet transform and traditional sparse representation with excellent fusion effect.