TY - JOUR
T1 - Retrieval of the height of buildings from worldView-2 multi-angular imagery using attribute filters and geometric invariant moments
AU - Licciardi, Giorgio A.
AU - Villa, Alberto
AU - Dalla Mura, Mauro
AU - Bruzzone, Lorenzo
AU - Chanussot, Jocelyn
AU - Benediktsson, Jn Atli
PY - 2012/2
Y1 - 2012/2
N2 - This paper proposes a novel approach to the retrieval of buildings' height from multi-angular high spatial resolution images. To achieve this task, we combined two main concepts: multilevel morphological attribute filters, used for the definition of the objects in the image, and geometric invariant moments exploited for the characterization of the spatial properties of the previously detected shapes. The main concept of this study relies on the spatial properties of very high resolution images acquired from different angles of view. In particular, if we model the urban environment as an ensemble of vertical and horizontal surfaces, we can assume that the shapes related to the horizontal surfaces (i.e. the top of the buildings) do not suffer any relevant spatial distortion if detected from two angles of view, while vertical surfaces present strong changes in shape. Starting from this assumption, once each shape in each angular images has been spatially characterized, it is possible to identify univocally the same horizontal surface (i.e. the roof of a building) in each angular image. Finally, the knowledge of the acquisition angles permits the retrieval of the buildings height using simple trigonometric calculations. In this paper the proposed approach has been successfully applied to a WorldView-2 (WV2) very high resolution dataset composed by five angular images.
AB - This paper proposes a novel approach to the retrieval of buildings' height from multi-angular high spatial resolution images. To achieve this task, we combined two main concepts: multilevel morphological attribute filters, used for the definition of the objects in the image, and geometric invariant moments exploited for the characterization of the spatial properties of the previously detected shapes. The main concept of this study relies on the spatial properties of very high resolution images acquired from different angles of view. In particular, if we model the urban environment as an ensemble of vertical and horizontal surfaces, we can assume that the shapes related to the horizontal surfaces (i.e. the top of the buildings) do not suffer any relevant spatial distortion if detected from two angles of view, while vertical surfaces present strong changes in shape. Starting from this assumption, once each shape in each angular images has been spatially characterized, it is possible to identify univocally the same horizontal surface (i.e. the roof of a building) in each angular image. Finally, the knowledge of the acquisition angles permits the retrieval of the buildings height using simple trigonometric calculations. In this paper the proposed approach has been successfully applied to a WorldView-2 (WV2) very high resolution dataset composed by five angular images.
KW - Buildings height retrieval
KW - invariant moments
KW - morphological attribute filters
KW - multiangular imaging
UR - http://www.scopus.com/inward/record.url?scp=84857730219&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2012.2184269
DO - 10.1109/JSTARS.2012.2184269
M3 - Article
AN - SCOPUS:84857730219
SN - 1939-1404
VL - 5
SP - 71
EP - 79
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
IS - 1
M1 - 6146382
ER -