Evaluation of image fusion quality based on EM algorithm

The purpose of the research is to put forward a method for quantitatively evaluating the quality of a image obtained by fusing several images. The method of the research is to model the image edge intensity using a mixture Rayleigh probability density functions(pdfs). The parameters and weights of mixture terms in the mixture model can be obtained using the EM iterative algorithm. The term with the smallest parameter corresponds to the weak edges, or the low-frequency background fluctuation. The term with the largest parameter corresponds to the strong edges. Therefore, the smallest variance parameter is considered as the noise variance estimation. Thus the blind estimation of the noise can be realized. And the largest variance parameter can be used to monitor the blurring. The results and conclusions of the research are that the image quality can be evaluated by studying the change of parameters in the mixture model. Compared with other image quality evaluation methods, this technique only needs the images to be evaluated and does not use detailed information about the formation of the images, and need not transform the images. The approach can be employed to estimate the smaller noise. These are the advantages of the approach. The investigation shows that this technique is quite robust and has low dependency on the image under evaluation.