查看文章

Image fusion method can provide a high-quality image by merging the multiple features of different source images, and how to effectively evaluate the quality (informativeness) of image features is an important issue for image fusion. Because a considerable amount of imprecise and uncertain information exists in image fusion processes, this paper proposes a framework based on fuzzy set theory to handle the vague features, and a set of hybrid optimization methods is also designed to improve the performance. First, the two-scale decomposition method is utilized to decompose the source images and obtain a set of corresponding subimages. Second, fuzzy set theory and local spatial frequency are employed to generate preliminary decision maps by evaluating the pixel quality of the subimages. Third, a morphological method and consistency verification are utilized to optimize the decision maps to extract the …