Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Journal of Applied Sciences
  Year: 2010 | Volume: 10 | Issue: 19 | Page No.: 2241-2250
DOI: 10.3923/jas.2010.2241.2250
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Effects of Hyperspectral Data Transformations on Urban Inter-class Separations using a Support Vector Machine

M.A. Misman, H.Z.M. Shafri and Raja M. Kamil Raja Ahmad

Abstract:
This study investigated the performance of different data types used in a hyperspectral data classification process. Data in the form of spectral reflectance, first derivative spectra and wavelet coefficients were used as inputs for the Support Vector Machine (SVM) algorithm used to classify five different classes. The first derivative spectra gave a lower classification accuracy (35.6%) than the spectral reflectance (82%) and the use of wavelet coefficients further improved the classification accuracy to 100%. Proper selection of the wavelet transformation method, the mother wavelet, the number of vanishing moments and the decomposition level could improve classification accuracy. In summary, wavelet coefficients could maximise discrimination capability as compared to the spectral reflectance and first derivative spectra.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    A New Bands Selection Algorithm for Hyperspectral Image using Hyperspectral Derivative on Clifford Manifold
  •    Improving Accuracy of Intention-Based Response Classification using Decision Tree
  •    Texture Characterisation and Classification Using Full Wavelet Decomposition
  •    Speech Recognition Algorithm of Parallel Subband HMM Based on Wavelet Analysis and Neural Network
  •    Texture Classification Based on Extraction of Skeleton Primitives Using Wavelets
How to cite this article:

M.A. Misman, H.Z.M. Shafri and Raja M. Kamil Raja Ahmad, 2010. Effects of Hyperspectral Data Transformations on Urban Inter-class Separations using a Support Vector Machine. Journal of Applied Sciences, 10: 2241-2250.

DOI: 10.3923/jas.2010.2241.2250

URL: https://scialert.net/abstract/?doi=jas.2010.2241.2250

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 

Curve Bottom