Overview of Hyperspectral Image Classification

Joint Authors

Lv, Wenjing
Wang, Xiaofei

Source

Journal of Sensors

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-07-08

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Civil Engineering

Abstract EN

With the development of remote sensing technology, the application of hyperspectral images is becoming more and more widespread.

The accurate classification of ground features through hyperspectral images is an important research content and has attracted widespread attention.

Many methods have achieved good classification results in the classification of hyperspectral images.

This paper reviews the classification methods of hyperspectral images from three aspects: supervised classification, semisupervised classification, and unsupervised classification.

American Psychological Association (APA)

Lv, Wenjing& Wang, Xiaofei. 2020. Overview of Hyperspectral Image Classification. Journal of Sensors،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1190454

Modern Language Association (MLA)

Lv, Wenjing& Wang, Xiaofei. Overview of Hyperspectral Image Classification. Journal of Sensors No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1190454

American Medical Association (AMA)

Lv, Wenjing& Wang, Xiaofei. Overview of Hyperspectral Image Classification. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1190454

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1190454