Title :
Object-Based Spatial Feature for Classification of Very High Resolution Remote Sensing Images
Author :
Penglin Zhang ; Zhiyong Lv ; Wenzhong Shi
Author_Institution :
Sch. of Remote Sensing & Inf. Eng., Wuhan Univ., Wuhan, China
Abstract :
This letter presents a novel spatial feature called object correlative index (OCI) to enhance the classification of very high resolution images. This novel method considers the property of an image object based on spectral similarity to construct a useful OCI to describe the spatial information objectively. Compared with the generic features widely used in image classification, the classification approach based on the OCI spatial feature results in higher classification accuracy than those approaches that only consider spectral features or pixelwise spatial features, such as the pixel shape index and mathematical morphology profiles. Experiments are conducted on QuickBird satellite image and aerial photo data, and results confirm that the proposed method is feasible and effective.
Keywords :
geophysical image processing; geophysical techniques; image classification; remote sensing; OCI spatial feature; QuickBird satellite image; aerial photo data; generic features; image object property; mathematical morphology profiles; object correlative index; object-based spatial feature; pixel shape index; pixelwise spatial features; remote sensing image classification; very high resolution remote sensing images; Accuracy; Feature extraction; Remote sensing; Spatial resolution; Support vector machines; Training; Classification of very high resolution (VHR) image; object correlative index (OCI); spatial feature; spectral feature;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2013.2262132