An efficient hierarchical hyperspectral image classification using binary quaternion-moment-preserving thresholding technique

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2, Issue , 2009, Pages

  Chang, Lena ^a   Cheng, Ching Min ^a   Chang, Yang Lang ^b  

^a NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

^b NATIONAL TAIPEI UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE IMAGES; HIGH-DIMENSIONAL IMAGES; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGE CLASSIFICATION; IMAGE FEATURES; MAXIMUM CORRELATIONS; SIMULATION RESULT; SPECTRAL CHARACTERISTICS; THRESHOLDING TECHNIQUES; UNSUPERVISED CLASSIFICATION;

GEOLOGY; IMAGE ANALYSIS; IMAGE CLASSIFICATION; REMOTE SENSING;

INDEPENDENT COMPONENT ANALYSIS;

EID: 77951105703     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2009.5418068     Document Type: Conference Paper

References (5)

1. Lena Chang and C. M. Cheng, "A combined signal subspace projection and partial filtering approach to target detection for hyperspectral images," proc. of IGARSS 2006.
2. Lena Chang, "Multispectral Image Compression Using Eigen-region-based Segmentation," Pattern Recognition, Vol.37, No.6, pp.1233-1243, 2004. (Pubitemid 38549822)
3. AVIRIS Images Website, http://aviris.jpl.nasa.gov
4. S. C. Pei and C. M. Cheng, "Color image processing by using binary quaternion-moment-preserving thresholding technique," IEEE Trans. on Image Processing, vol.8, no.5, pp.1-16, 1999.
5. Y. L. Chang, C. C. Han, and et. al., "A modular eigenspace scheme for high dimensional data classification," Future Generation Computer Systems, pp. 1131-1143, 2004.