抄録
We previously proposed a method of automatically constructing image transformations which consist of a sequence of several given image filters. They are optimized to approximate the transformation from an original image to its target one using a genetic algorithm where the target image is an ideally processed one made manually. In this paper, we propose an extended method ACTIT. We put image filters having several inputs together into tree-structures.The leaf nodes of a tree are the original images and other nodes are the image filters. And the output of the root node means the output of a whole image transformation. To get good output images, the tree is optimized by genetic programming. In this way, we construct complex image transformations which cannot be constructed by a sequence of image filters. We applied ACTIT to medical image processing and proved that it is useful for automating the construction of image transformations.
