Abstract
How to obtain efficient fusion coefficients is the key problem in image fusion processing. In terms of the statistical characteristic of images,CP decomposition and GHM multiwavelets are constructed and using multiwavelet domain HMT models to capture the dependencies of coefficients in this article. Furthermore,the evolution computation idea—Immune clonal selection (ICS) algorithm is introduced to optimize the fusion coefficients for better fusion results. Fusion performance is evaluated through subjective inspection,as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional wavelets and multiwavelet systems as information entropy (IE) values keep at a high level,and average grads (AG) values increase averagely about 1.3 and 2.3,respectively and standard differences (STD) values increase averagely about 8.0 and 8.8,respectively.
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