NDLI: Morphology-based structure-preserving projection for spectral–spatial feature extraction and classification of hyperspectral data

Content Provider	IET Digital Library
Author	Imani, Maryam Ghassemian, Hassan
Abstract	Incorporation of spatial information besides rich spectral information of hyperspectral image significantly enhances data classification accuracy. A morphology-based feature extraction and classification framework is proposed here, which includes the local neighbourhood information in a spatial window for extension of training set. The proposed method is morphology-based structure-preserving projection (MSPP) and tries to preserve the data structure in spectral–spatial feature space. Moreover, MSPP increases the class discrimination ability by defining a similarity matrix constructed by extended spectral–spatial training samples. The experimental results show the superiority of MSPP compared to some state-of-the-art classification methods from the classification accuracy point of view.
Starting Page	270
Ending Page	279
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 2, Feb (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.1431
Journal	IET Image Processing
Publisher Date	2018-07-08
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Class Discrimination Ability Computer Vision And Image Processing Technique Data Classification Accuracy Data Structure Data Structures Extended Spectral–spatial Training Samples Feature Extraction Hyperspectral Data Classification Hyperspectral Image Image Classification Image Recognition Local Neighbourhood Information Matrix Algebra Morphology-based Structure-preserving Projection MSPP Similarity Matrix Spatial Information Spatial Window Spectral Information Spectral-spatial Feature Space Spectral–spatial Feature Extraction Training Set Extension
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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