Segmentation driven by an iterative pairwise mutually best merge criterion
Andrea Baraldi, F. Parmiggiani · 2002
The iterative pairwise mutually best merge (IPMBM) segmentation algorithm extracts image regions characterized by low within-segment variance, IPMBM employs a new metric, called normalized vector distance (NVD), to perform a normalized comparison between a pair of multivalued vectors. IPMBM is robust and easy to use since only two parameters, both having an intuitive physical meaning, must be user-defined. Experimental results demonstrate that IPMBM is effective in real applications.