Lj. Guo et Jd. Haigh, A 3-DIMENSIONAL FEATURE SPACE ITERATIVE CLUSTERING METHOD FOR MULTISPECTRAL IMAGE CLASSIFICATION, International journal of remote sensing, 15(3), 1994, pp. 633-644
A practical method of three-dimensional feature space iterative cluste
ring (3D-FSIC) for image classification has been introduced, in which
the clustering iteration is performed in three-dimensional feature spa
ce rather than scanning the image pixel by pixel. This method permits
the cluster size and pixel frequency to be taken into account so that
a more advanced decision rule, the optimal multiple point reassignment
(OMPR) can be applied. The paper also provides a simple technique for
splitting a cluster based on the first principal component without pe
rforming principal component transformation. Finally, a classification
example using hue images as well as a discussion of the advantages of
using hue images in the 3D-FSIC classification is given.