Title :
Mixture models with higher order moments
Author :
Bosdogianni, Panagiota ; Petrou, Maria ; Kittler, Josef
Author_Institution :
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
fDate :
3/1/1997 12:00:00 AM
Abstract :
The authors present a novel method for mixed pixel classification where the classification of groups of mixed pixels is achieved by taking into consideration the higher order moments of the distributions of the pure and the mixed classes. The equations expressing the relationship between the higher order moments are used to augment the set of equations that express the relationship between the means only. The authors show that weighting these equations does not make the set of equations available less reliable. As a consequence, the number of equations can be increased and thus more classes than available bands can be identified. The method is exhaustively tested using simulated data and is also applied to real Landsat TM data for which ground data are available
Keywords :
geophysical signal processing; geophysical techniques; image classification; remote sensing; Landsat TM; geophysical measurement technique; groups of mixed pixels; higher order moments; image classification; land surface; mixed pixel classification; mixture model; multidimensional signal processing; multispectral remote sensing; optical imaging; terrain mapping; Equations; Geography; Image analysis; Probability density function; Random variables; Remote sensing; Satellites; Spectral analysis; Testing; Vegetation mapping;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on