关键词: 图像处理, 图像融合, 稀疏表示, 训练字典

Abstract: An image fusion algorithm is presented based on sparse representation and training dictionary in order to improve the fusion quality of multi-spectral image and panchromatic image. A new intensity component is firstly obtained by taking the method of smoothing filter-based intensity modulation on the original intensity component of the multi-spectral image. The panchromatic image and intensity component are obtained for their sparse coefficient through training dictionary which generated by randomly sampling raw patches. Then, the fused coefficient is obtained by the fusion rule which choosing spatial frequency maximum. Finally, the fused results are obtained through reconstruction and IHS inverse transformation. The improved algorithm has been tested on various multi-spectral and panchromatic satellite remote sensing images for different areas. The experimental results prove that the proposed method can improve the spatial resolution and better maintain the spectral characteristics.

Key words: image processing, image fusion, sparse representation, training dictionary