In order to solve the problem that fusion rules of existing image fusion methods can not be adjusted adaptively according to successive application target of the fusion image, and advantages of different fusion algorithm can not be integrated, an image fusion framework based on data assimilation and differential evolution algorithm (DE) is proposed. In this framework, nonsubsampled contourlet transform is used as model operator and discrete wavelet transform with DBSS(2,2)as observer operator. The objective function is composed of weight sum of indices, which are determined according to their relations with following application, and DE is employed to obtain proper image. Two groups of experiments with the help of the quantitative parameters(entropy, average gradient, standard deviation spatial frequency and interactive entropy of rms)and visual analysis verify feasibility of the framework.