Extraction of Earth Surface Texture Features from Multispectral Remote Sensing Data
Joint Authors
Gao, Feng
Zhang, Zhenxing
Ma, Bin
Zhang, Zhiqiang
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-25
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Earth surface texture features referring to as visual features of homogeneity in remote sensing images are very important to understand the relationship between surface information and surrounding environment.
Remote sensing data contain rich information of earth surface texture features (image gray reflecting the spatial distribution information of texture features, for instance).
Here, we propose an efficient and accurate approach to extract earth surface texture features from remote sensing data, called gray level difference frequency spatial (GLDFS).
The gray level difference frequency spatial approach is designed to extract multiband remote sensing data, utilizing principle component analysis conversion to compress the multispectral information, and it establishes the gray level difference frequency spatial of principle components.
In the end, the texture features are extracted using the gray level difference frequency spatial.
To verify the effectiveness of this approach, several experiments are conducted and indicate that it could retain the coordination relationship among multispectral remote sensing data, and compared with the traditional single-band texture analysis method that is based on gray level co-occurrence matrix, the proposed approach has higher classification precision and efficiency.
American Psychological Association (APA)
Zhang, Zhenxing& Gao, Feng& Ma, Bin& Zhang, Zhiqiang. 2018. Extraction of Earth Surface Texture Features from Multispectral Remote Sensing Data. Journal of Electrical and Computer Engineering،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184577
Modern Language Association (MLA)
Zhang, Zhenxing…[et al.]. Extraction of Earth Surface Texture Features from Multispectral Remote Sensing Data. Journal of Electrical and Computer Engineering No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1184577
American Medical Association (AMA)
Zhang, Zhenxing& Gao, Feng& Ma, Bin& Zhang, Zhiqiang. Extraction of Earth Surface Texture Features from Multispectral Remote Sensing Data. Journal of Electrical and Computer Engineering. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1184577
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1184577