Synthesis performance evaluation of image fusion based on the ameliorating degree of grey euclid incidence

In the computational process of the traditional degree of grey incidence, the degree of grey incidence is the average of the incidence coefficients in each spot between the comparison sequence and the reference sequence. so long as the incidence coefficient´s algebra in each spot maintains invariable, no matter then how the incidence coefficients in each spot does fluctuate, the degree of grey incidence does not change. This is obviously unreasonable and may be the wrong result in the appraisal. Based on this, the Ameliorating degree of grey Euclid incidence is put up and its characteristic is analyzed in this paper. Moreover, the synthesis performance evaluation of image fusion based on the ameliorating degree of grey euclid incidence is advanced. The proposed approach combines the apriori knowledge and quantization evaluation and realizes the quality synthetic evaluation of image fusion. Extensive experimental analysis shows that the proposed approach performs better on quantization, prevision and objectivity, reliability. The advantages above make it apply properly to fusion system with feedback capability and it enriches and perfects the image fusion system.