Binary coding based feature extraction in remote sensing high dimensional data

被引：27

作者：

Imani, Maryam ^{[1
]}

Ghassemian, Hassan ^{[1
]}

机构：

[1] Tarbiat Modares Univ, Fac Elect & Comp Engn, Tehran, Iran

来源：

INFORMATION SCIENCES | 2016年 / 342卷

关键词：

Binary coding; Feature extraction; Classification; High dimensional data; Small sample size situation; WEIGHTED FEATURE-EXTRACTION; HYPERSPECTRAL-IMAGE; DISCRIMINANT-ANALYSIS; CLASSIFICATION; RELEVANCE;

D O I：

10.1016/j.ins.2016.01.032

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A binary coding based feature extraction (BCFE) method is proposed in this paper. In the BCFE method, the spectral signature of each pixel of hyperspectral image is partitioned into some equal segments. Then, the weighted mean of spectral bands in each segment is considered as an extracted feature. BCFE uses a new method for calculation of weights. In BCFE, the binary codes of class means are obtained. Then, the information contained in the binary values and the edges of class means is used for calculation of weight in each band. The experimental results on three real hyperspectral images show the better performance of BCFE compared to some popular and state-of-the-art feature extraction methods, from the accuracy and computation time point of views, in a small sample size situation. (C) 2016 Elsevier Inc. All rights reserved.

引用

页码：191 / 208

页数：18

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