ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2015, Vol. 52 ›› Issue (4): 952-959.doi: 10.7544/issn1000-1239.2015.20131736

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

Lin Suzhen, Zhu Xiaohong, Wang Dongjuan, Wang Xiaoxia   

  1. (Key Laboratory of Instrumentation Science and Dynamic Measurement(North University of China), Ministry of Education, Taiyuan 030051)
  • Online:2015-04-01

Abstract: 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.

Key words: image fusion, multi-band images, embedded multi-scale transform (EMT), disjunctive combination, quad-tree (QT), support value transform (SVT)

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