A new image fusion method based on Compressed Sensing
Smart and Sustainable City 2013(2013)
摘要
In order to solve the problem that the traditional image fusion methods have more sampling points, the paper proposed a new image fusion method based on Compressed Sensing (CS) which builds the new sampling mode combined with CS. We firstly obtain the linear measurements in compressed domain based on random sampling mode, and then fuse the linear measurements directly with a simple but efficient weighted average method, and recover the fused image by solving the minimization problem at the fusing end. The proposed method can recover the fusion image with less measurement due to the compressive sampling. This paper proves the superiority of the proposed method by three simulation experiments, and the results show that this method can achieve a favorable fusion effect like the traditional methods.
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关键词
compressed sensing,image fusion,image sampling,minimisation,compressed sensing,image fusion method,linear measurement,minimization problem,random sampling mode,weighted average method,Compressed Sensing,Image Fusion,Random Sampling
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