A MULTISCALE ALGORITHM FOR IMAGE SEGMENTATION BY VARIATIONAL METHOD

被引:141
作者
KOEPFLER, G
LOPEZ, C
MOREL, JM
机构
[1] COGNITECH INC, SANTA MONICA, CA 90405 USA
[2] UNIV PARIS 09, CEREMADE, F-75775 PARIS 16, FRANCE
关键词
VARIATIONAL METHODS; NONNUMERICAL ALGORITHM; IMAGE PROCESSING; TEXTURE DISCRIMINATION;
D O I
10.1137/0731015
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Most segmentation algorithms are composed of several procedures: split and merge, small region elimination, boundary smoothing,..., each depending on several parameters. The introduction of an energy to minimize leads to a drastic reduction of these parameters. The authors prove that the most simple segmentation tool, the ''region merging'' algorithm, made according to the simplest energy, is enough to compute a local energy minimum belonging to a compact class and to achieve the job of most of the tools mentioned above. The authors explain why ''merging'' in a variational framework leads to a fast multiscale, multichannel algorithm, with a pyramidal structure. The obtained algorithm is O(n ln n), where n is the number of pixels of the picture. This fast algorithm is applied to make grey level and texture segmentation and experimental results are shown.
引用
收藏
页码:282 / 299
页数:18
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