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Image Segmentation Analysis for NASA Earth Science ApplicationsNASA collects large volumes of imagery data from satellite-based Earth remote sensing sensors. Nearly all of the computerized image analysis of this data is performed pixel-by-pixel, in which an algorithm is applied directly to individual image pixels. While this analysis approach is satisfactory in many cases, it is usually not fully effective in extracting the full information content from the high spatial resolution image data that s now becoming increasingly available from these sensors. The field of object-based image analysis (OBIA) has arisen in recent years to address the need to move beyond pixel-based analysis. The Recursive Hierarchical Segmentation (RHSEG) software developed by the author is being used to facilitate moving from pixel-based image analysis to OBIA. The key unique aspect of RHSEG is that it tightly intertwines region growing segmentation, which produces spatially connected region objects, with region object classification, which groups sets of region objects together into region classes. No other practical, operational image segmentation approach has this tight integration of region growing object finding with region classification This integration is made possible by the recursive, divide-and-conquer implementation utilized by RHSEG, in which the input image data is recursively subdivided until the image data sections are small enough to successfully mitigat the combinatorial explosion caused by the need to compute the dissimilarity between each pair of image pixels. RHSEG's tight integration of region growing object finding and region classification is what enables the high spatial fidelity of the image segmentations produced by RHSEG. This presentation will provide an overview of the RHSEG algorithm and describe how it is currently being used to support OBIA or Earth Science applications such as snow/ice mapping and finding archaeological sites from remotely sensed data.
Document ID
20100014876
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Tilton, James C.
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Date Acquired
August 24, 2013
Publication Date
March 27, 2010
Subject Category
Earth Resources And Remote Sensing
Meeting Information
Meeting: Capital Science 2010
Location: Arlington, VA
Country: United States
Start Date: March 27, 2010
End Date: March 28, 2010
Sponsors: National Science Foundation
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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