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Proceedings Paper

Segmentation of remotely sensed images by MDL-principled polygon map grammar
Author(s): HePing Pan; Wolfgang Foerstner
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Paper Abstract

Polygon map grammar -- a generic structure model of polygon maps -- has been developed to an operational level for landuse mapping from remotely sensed images. This grammar enables us to simulate stochastic structures of polygon maps, and thus to simulate ideal and real images of landuse fields. These images provide fully controlled cases for testing image segmentation algorithms. We have developed a general segmentation algorithm which cascades an information-preserving smoothing filter, an edge-preserving smoothing filter, and explicit MDL-based region merging. With both simulated and real images, this algorithm proved to be objective and robust, yielding good results. Using crack edges a mechanism exists and is developed to vectorize raster segmented image to a polygon map data structure -- polyplex. With this data structure, the high-level structure model -- polygon map grammar -- is used to predict missing edges that are not caused by image intensity but are truly not detectable by remote sensors. This paper describes a complete case of this grammar and its application, and a number of basic general mechanisms.

Paper Details

Date Published: 17 August 1994
PDF: 8 pages
Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); doi: 10.1117/12.182905
Show Author Affiliations
HePing Pan, Univ. Bonn (Germany)
Wolfgang Foerstner, Univ. Bonn (Germany)


Published in SPIE Proceedings Vol. 2357:
ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision
Heinrich Ebner; Christian Heipke; Konrad Eder, Editor(s)

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