基于稀疏K-SVD字典的图像融合方法

A Novel Image Fusion Method Based on The Sparse K-SVD Dictionary

稀疏K-SVD算法是一种字典生成方法,它将解析字典的结构性与学习字典的自适应性进行了有效的结合,得到的字典对信号具有很好的稀疏表示能力,理论上,该字典的性能比其他字典更好.为了进一步提高图像融合方法的性能,提出了一种基于稀疏K-SVD字典的图像融合方法.最后通过实验验证了该算法的有效性.

The sparse K-SVD algorithm is a method that can produce a dictionary combined the structure of the analytical dictionaries and the adaption of the trained dictionaries effectively,resulting a dictionary that has a good sparse representation capability.Theoretically,this method can achieve better result than other methods.In order to further improve the efficiency of the image fusion method,we propose a novel image fusion method based on the sparse K-SVD dictionary.Finally,the experimental results prove the effectiveness of the algorithm.