A Novel Gray Image Representation Method Based on NAM Using Nonoverlapping Square Subpatterns

Abstract

In this paper, we propose a novel gray image representation method based on the non-symmetry and anti-packing model (NAM) by using the nonoverlapping square subpatterns, which is called the square NAM for gray images (SNAMG) representation method. Also, a SNAMG representation algorithm is put forward and the storage structures, the total data amount, and the time complexity of the proposed algorithm are analyzed in detail. By taking some standard gray images, such as ‘F16’ and ‘Peppers’, as the typical test objects, and comparing the proposed algorithm with those of the triangle NAM for gray images (TNAMG) and the classic linear quadtree (LQT), the theoretical and experimental results show that the former is obviously superior to the latter with respect to the numbers of subpatterns (nodes) and the data storage, and therefore it is a better method to represent the gray image pattern.