Feature extraction, anomaly, and change detection on WorldView-2 imagery by hierarchical image segmentation: a study

Lakshman Prasad; James Theiler; Matthew Fair; Sriram Swaminarayan

doi:10.1117/12.919295

24 May 2012 Feature extraction, anomaly, and change detection on WorldView-2 imagery by hierarchical image segmentation: a study

Lakshman Prasad, James Theiler, Matthew Fair, Sriram Swaminarayan

Author Affiliations +

Proceedings Volume 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII; 83901U (2012) https://doi.org/10.1117/12.919295
Event: SPIE Defense, Security, and Sensing, 2012, Baltimore, Maryland, United States

Abstract

We study spatio-spectral feature extraction and image-adaptive anomaly and change detection on 8-band WorldView 2 imagery using a hierarchical polygonal image segmentation scheme. Features are represented as polygons with spectral and structural attributes, along with neighborhood structure and containment hierarchy for contextual feature identification. Further, the hierarchical segmentation provides multiple, coarse-scale, sub-backgrounds representing relatively uniform regions, which localize and simplify the spectral distribution of an image. This paves the way for facilitating anomaly and change detection when restricted to the contexts of these backgrounds. For example, forestry, urban areas, and agricultural land have very different spatio-spectral characteristics and their joint contribution to the image statistics can result in a complex distribution against which detecting anomalies could in general be a challenging problem. Our segmentation scheme provides sub-regions in the later stages of the hierarchy that correspond to homogeneous areas of an image while at the same time allowing inclusion of distinctive small features embedded in these regions. The exclusion of other image areas by focusing on these sub-backgrounds helps discover these outliers more easily with simpler methods of discrimination. By selecting appropriate bands in WorldView2 imagery, the above approach can be used to achieve fine spatio-spectral control in searching and characterizing features, anomalies, and changes of interest. The anomalies and changes are also polygons, which have spectral and structural attributes associated with them, allowing further characterization in the larger context of the image. The segmentation and feature detections can be used as multiple layers in a Geospatial Information System (GIS) for annotating imagery.

Citation Download Citation

Lakshman Prasad, James Theiler, Matthew Fair, and Sriram Swaminarayan "Feature extraction, anomaly, and change detection on WorldView-2 imagery by hierarchical image segmentation: a study", Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83901U (24 May 2012); https://doi.org/10.1117/12.919295

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