BINARY CODES K-MODES CLUSTERING FOR HSI SEGMENTATION

被引：0
|
作者：
Berthier, Michel [1 ]
El Asmar, Saadallah [1 ]
Frelicot, Carl [1 ]
机构：
[1] Univ La Rochelle, Lab Math Image & Applicat, La Rochelle, France
来源：
2016 IEEE 12TH IMAGE, VIDEO, AND MULTIDIMENSIONAL SIGNAL PROCESSING WORKSHOP (IVMSP) | 2016年
关键词：
Hyperspectral image segmentation; Binary codes; Generalized Hamming distance; k-modes clustering; HYPERSPECTRAL IMAGES; ALGORITHM; CLASSIFICATION;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
An new pixel unsupervised hyperspectral image (HSI) segmentation method is proposed. It relies on a binary incoding of spectral reflectance curve variations of pixels that allows to consider HSI segmentation as a clustering problem in the feature set of binary strings. Using a generalized Hamming distance, a k-modes algorithm is applied to obtain a cluster partionning of the HSI with no use of any spatial information.
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页数：5
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