PERSISTENT SCATTERER AIDED FACADE LATTICE EXTRACTION IN SINGLE AIRBORNE OPTICAL OBLIQUE IMAGES
We present a new method to extract patterns of regular facade structures from single optical oblique images. To overcome the missing three-dimensional information we incorporate structural information derived from Persistent Scatter (PS) point cloud data into our method. Single oblique images and PS...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2015-03-01
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/II-3-W4/197/2015/isprsannals-II-3-W4-197-2015.pdf |
Summary: | We present a new method to extract patterns of regular facade structures from single optical oblique images. To overcome the missing
three-dimensional information we incorporate structural information derived from Persistent Scatter (PS) point cloud data into our
method. Single oblique images and PS point clouds have never been combined before and offer promising insights into the compatibility
of remotely sensed data of different kinds. Even though the appearance of facades is significantly different, many characteristics of the
prominent patterns can be seen in both types of data and can be transferred across the sensor domains. To justify the extraction based
on regular facade patterns we show that regular facades appear rather often in typical airborne oblique imagery of urban scenes. The
extraction of regular patterns is based on well established tools like cross correlation and is extended by incorporating a module for
estimating a window lattice model using a genetic algorithm. Among others the results of our approach can be used to derive a deeper
understanding of the emergence of Persistent Scatterers and their fusion with optical imagery. To demonstrate the applicability of the
approach we present a concept for data fusion aiming at facade lattices extraction in PS and optical data. |
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ISSN: | 2194-9042 2194-9050 |