Existing classification methods which are based on the homogeneous-region mostly involve the best segmentation scale choice. Using the so-called best segmentation scale to respond the subjective defined objects, it would not be the best way for classification. Therefore we propose a simple classification method with high precision. It is a new kind of multi-scale homogeneous-region model, fully uses the longitudinal information which the homogeneous-region model provides, and adopts the scale-span classification method based on decision tree to improve the accuracy, rather than directly carrying on the best scale choice. The experimental result proves the scale-span method is more accurate than sole scale lassification.
The Scale-Span Classification Research for Multispectral Images Based on the Homogeneous-Region
2008 Congress on Image and Signal Processing ; 2 ; 171-175
2008-05-01
2590801 byte
Conference paper
Electronic Resource
English
ATR Applied to Multispectral Images Classification Based on KLT
British Library Online Contents | 2003
|Robust Photometric Invariant Region Detection in Multispectral Images
British Library Online Contents | 2003
|