Multi-Band Image Fusion Based on Embedded Multi-Scale Transform

Multi-band images fusion can improve the effect of the target detection. In view of the differences among multi-band images often reduced by using the sequential fusion, a method of multi-band image fusion is proposed by embedded multi-scale transform (EMT) and local difference feature. The detailed procedure is shown as follows: Firstly, multi-band images are decomposed respectively with support value transform (SVT). Secondly, using the method of quad-tree (QT), the last layer of low-frequency image for most dispersed grey value image is decomposed into blocks which are regarded as the standard to decompose the others’ last layer of low-frequency image. Thirdly, using disjunctive combination of the possibility theory, corresponding blocks of the multi-band images are fused in feature-level. Then, all blocks are traversed to get low frequency fused block images which are mosaicked. Lastly, the final image is got through inverse transformation of mosaic image and support sequence fused image. The fused results of visible image, infrared medium-wave image and long-wave image show that: the effect is significant based on quad-tree decomposition; compared with the simple quad-tree decomposition fusion, the method of EMT successfully increases the edge intensity by 13.31%, the contrast ratio by 2.63%, the entropy by 4.26% and decreases the running time by 87.11%. Thus the validity of the method is proved.