A new IITNAM representation method of gray images

In this paper, inspired by the idea of the triangle and square packing problems, by using the combination of triangle subpatterns and square subpatterns, we propose a new representation method of gray images based on the triangular and square non-symmetry and anti-packing model (TSNAM). Also, we present a TSNAM representation algorithm of gray images and analyze the storage structures and the total data amount of the algorithm. By comparing the representation algorithm of the TSNAM with those of the latest improved indirect triangle non-symmetry and anti-packing model (IITNAM) and the conventional linear quadtree (LQT), the theoretical and experimental results in this paper show that the former can greatly reduce the numbers of subpatterns or nodes and simultaneously save the data storage much more effectively than the latter, and therefore it is a better method to represent gray images.