• A chromaticity difference-base...

Treffer: A chromaticity difference-based classification algorithm for imaging spectrometer data

Title:
A chromaticity difference-based classification algorithm for imaging spectrometer data
Authors:
ZHANG, Liangpei, LIN, Hui, LI, Deren
Source:
Object detection, classification, and tracking technologies (Wuhan, 22-24 October 2001)SPIE proceedings series. :165-170
Publisher Information:
Bellingham WA: SPIE, 2001.
Publication Year:
2001
Physical Description:
print, 14 ref
Original Material:
INIST-CNRS
Subject Terms:
Electronics, Electronique, Computer science, Informatique, Optics, Optique, Physics, Physique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Appariement image, Image matching, Banque image, Image databank, Banco imagen, Capteur imagerie hyperspectral, Hyperspectral imaging sensor, Sensor hiperespectral de formación de imágenes, Chromaticité, Chromaticity, Cromaticidad, Classification image, Image classification, Codage binaire, Binary coding, Codificación binaria, Formation image, Imaging, Formación imagen, Image numérique, Digital image, Imagen numérica, Mesure sans contact, Non contact measurement, Medida sin contacto, Méthode spectrale, Spectral method, Método espectral, Performance algorithme, Algorithm performance, Resultado algoritmo, Spectromètre, Spectrometer, Espectrómetro, Théorie classification, Classification theory, Teoría clasificación, Traitement image, Image processing, Procesamiento imagen, Télédétection, Remote sensing, Teledetección, Télémesure, Telemetry, Telemedida
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
National Laboratory for Information Engineering in Surveying, mapping and Remote Sensing, Wuhan University, Hong-Kong
Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Shatin, N.T., Hong-Kong
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=14056811
Rights:
Copyright 2002 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.14056811
Database:
PASCAL Archive

Weitere Informationen

Hyperspectral remote sensing image classification generally adopts a direct spectral matching method. It is, however, inconvenient in the classification calculation because the complete reference spectra are needed. In this work we have developed a new chromaticity difference-based classification algorithm, which can be used to classify imaging spectrometer image data. In calculation, the algorithm itself is not directly relating to the number of spectral wavebands. It only needs three chromaticity coordinate parameters for both the image spectrum and the reference spectrum to complete the final classification calculation. In addition, the classification threshold for the algorithm can be easily set according to the color science theory, therefore, the classification results from the algorithm is reliable. Through a comparison with SAM algorithm, the performance of the new chromaticity difference-based classification algorithm was proved to be as good as SAM algorithm, but our algorithm was relatively simpler and flexible.