@incollection{Bea1989c,
author = {Beaulieu, Jean-Marie},
title = {Segmentation Hi{\'e}rarchique de l'Image par Optimisation S{\'e}quentielle},
booktitle = {T{\'e}l{\'e}d{\'e}tection et Gestion des Ressources},
volume = {Vol. VI},
editor = {Bernier and Bonn and Gagnon},
publisher = {Association Qu{\'e}b{\'e}coise de T{\'e}l{\'e}d{\'e}tection, Qu{\'e}bec},
address = {Ste-Foy, Qu{\'e}bec},
pages = {245-251},
year = {1989},
month = {},
url = {},
isbn = {},
doi = {},
mypdf = {9},
abstract = {A hierarchical segmentation algorithm based upon step-wise optimization is presented. The algorithm starts with an initial picture partition, and at each iteration, the two most similar segments are merged by optimizing a "step-wise criterion". This yields a hierarchical decomposition of the picture, which is data driven with no restriction on segment shapes. The algorithm is designed so as to reduce the computing
time. Hence, the fact that a segment merge affects only the surrounding segments is exploited. Good results are produced because of the global and gradual manner of the sequential optimization.},
keywords = {}
}