An improved BPD-based triangle NAM for image representation

Designing efficient image representation is an important issue in different fields of multimedia information. In this paper, inspired by the idea of the triangle and rectangle packing problems and by using the combination of triangle subpatterns and rectangle subpatterns, we propose an improved BPD-based triangle non-symmetry and anti-packing model (NAM) for image representation, which is called ITNAM representation. Also, we present an ITNAM representation algorithm of gray images and analyze the storage structures and the total data amount of the algorithm. By comparing the ITNAM representation algorithm with the latest TNAM and the conventional LQT representation algorithms, the theoretical and experimental results 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.