Study on an Improved Algorithm for TNAM of Gray Images
The image representation is one of the most important research contents in robotics,image processing,pattern recognition,and so on. By studying the image representation methods of the popular linear quadtree and the Triangle Non-symmetry and Anti-packing pattern representation Model (TNAM),in this paper,we present an improved algorithm for TNAM of gray images. Also,we analyze the storage structure and the total data amount of the improved algorithm. The theoretical and experimental results presented in this paper show that the improved representation method for TNAM of gray images can reduce the data storage much more effectively than the representation methods of the popular linear quadtree and the TNAM and it is a better method to represent the gray image pattern.