Dimensionality reduction of hyperspectral data using spectral fractal feature

被引：11

作者：

Mukherjee, Kriti ^{[1
]}

Ghosh, Jayanta Kumar ^{[1
]}

Mittal, Ramesh Chand ^{[2
]}

机构：

[1] Indian Inst Technol Roorkee, Dept Civil Engn, Roorkee 247667, Uttar Pradesh, India

[2] Indian Inst Technol Roorkee, Dept Math, Roorkee 247667, Uttar Pradesh, India

来源：

GEOCARTO INTERNATIONAL | 2012年 / 27卷 / 06期

关键词：

hyperspectral data; fractal dimension; spectral response curve; power spectrum; CLASSIFICATION;

D O I：

10.1080/10106049.2011.642411

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

A new approach for dimensionality reduction of hyperspectral data has been proposed in this article. The method is based on extraction of fractal-based features from the hyperspectral data. The features have been generated using spectral fractal dimension of the spectral response curves (SRCs) after smoothing, interpolating and segmenting the curves. The new features so generated have then been used to classify hyperspectral data. Comparing the post classification accuracies with some other conventional dimensionality reduction methods, it has been found that the proposed method, with less computational complexity than the conventional methods, is able to provide classification accuracy statistically equivalent to those from conventional methods.

引用

页码：515 / 531

页数：17