Image fusion algorithm based on WNMF and regional fractal dimension

The non-negative matrix factorization based fusion algorithm can not extract details from source images effectively. In order to improve this defect of non-negative matrix factorization, a novel image fusion algorithm for infrared and visible images based on weighted non-negative matrix factorization and regional fractal dimension is proposed. The properties of regional fractal dimensions are researched, and the weighted coefficients are obtained through regional fractal dimensions on different scales. The weighted coefficients are designed for emphasizing the edges and small areas of the source images, so the fusion result that is more comfortable to observe and contains more details is obtained. Compared with other methods based on traditional non-negative matrix factorization, the proposed algorithm improves the visual effect and the average gradient of the fusion result is improved by more than 19%.