Numerical images are becoming more and more important and an increasing emphasis on multimedia applications has resulted in large volumes of images. However, images need a large memory space to be stored, so their efficient storage and retrieval generate challenges to the database community. This paper proposes a new algorithm for an efficient storage of sets of images. It is based on a version approach used in databases. It shows how to store and operate on similar images; two images are defined as similar if the quad-trees encoding them have only few different nodes. A data structure called Generic Quad-Tree (GQT) is proposed. It optimizes the memory space required to store similar images and allows an efficient navigation among them. An Image Tree stores the ancestors and descendants of an image, like a version hierarchy. Using the Image Tree, the Generic Quad-Tree allows an image to share common parts with its ancestors and descendants. The GQT approach and some algorithms for reading, modifying or removing images from the Generic Quad-Tree are described. Examples using black and white images and gray scale images are presented.
Generic Quad-Tree; operations on quad-trees; image representation; image comparison; optimization of memory space; image processing application
