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Summary: 1
Automatic Detection of Geospatial Objects Using
Multiple Hierarchical Segmentations
H. G¨okhan Akc¸ay and Selim Aksoy, Member, IEEE
Abstract--Object-based analysis of remotely sensed imagery
provides valuable spatial and structural information that are
complementary to pixel-based spectral information in classifi-
cation. In this paper, we present novel methods for automatic
object detection in high-resolution images by combining spec-
tral information with structural information exploited using
image segmentation. The proposed segmentation algorithm uses
morphological operations applied to individual spectral bands
using structuring elements in increasing sizes. These operations
produce a set of connected components forming a hierarchy
of segments for each band. A generic algorithm is designed to
select meaningful segments that maximize a measure consisting
of spectral homogeneity and neighborhood connectivity. Given
the observation that different structures appear more clearly
at different scales in different spectral bands, we describe a
new algorithm for unsupervised grouping of candidate segments
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