Automated Detection of Arbitrarily Shaped Buildings in Complex Environments From Monocular VHR Optical Satellite Imagery

Ok, Ali Ozgun
Senaras, Caglar
Yuksel, Baris
This paper introduces a new approach for the automated detection of buildings from monocular very high resolution (VHR) optical satellite images. First, we investigate the shadow evidence to focus on building regions. To do that, we propose a new fuzzy landscape generation approach to model the directional spatial relationship between buildings and their shadows. Once all landscapes are collected, a pruning process is developed to eliminate the landscapes that may occur due to non-building objects. The final building regions are detected by GrabCut partitioning approach. In this paper, the input requirements of the GrabCut partitioning are automatically extracted from the previously determined shadow and landscape regions, so that the approach gained an efficient fully automated behavior for the detection of buildings. Extensive experiments performed on 20 test sites selected from a set of QuickBird and Geoeye-1 VHR images showed that the proposed approach accurately detects buildings with arbitrary shapes and sizes in complex environments. The tests also revealed that even under challenging environmental and illumination conditions, reasonable building detection performances could be achieved by the proposed approach.


Automatic building detection from high resolution satellite images
Koc, D; Turker, M (2005-06-11)
An approach was developed to update the buildings of existing vector database from high resolution satellite images using image classification, Digital Elevation Models (DEM) and object extraction techniques. First, the satellite image is classified using the Maximum Likelihood Classifier (MLC). The classified output provides the shapes and the approximate locations of the buildings. Next, a normalized Digital Surface Model (nDSM) is generated by subtracting the Digital Terrain Model (DTM) from the Digital ...
Building Detection With Decision Fusion
Senaras, Caglar; Ozay, Mete; Yarman Vural, Fatoş Tunay (Institute of Electrical and Electronics Engineers (IEEE), 2013-6)
A novel decision fusion approach to building detection problem in VHR optical satellite images is proposed. The method combines the detection results of multiple classifiers under a hierarchical architecture, called Fuzzy Stacked Generalization (FSG). After an initial segmentation and pre-processing step, a large variety of color, texture and shape features are extracted from each segment. Then, the segments, represented in different feature spaces are classified by different base-layer classifiers of the F...
Sea Detection on High-Resolution Panchromatic Satellite Images Using Texture and Intensity
Besbinar, Beril; Alatan, Abdullah Aydın (2014-01-01)
In this paper, a two-stage sea-land mask detection algorithm on high resolution panchromatic images is proposed. An initial mask is generated using texture features in the first stage and this mask is refined by using intensity values in the second stage. Image is divided into windows and the Local Binary Patterns (LBP) histograms, evaluated at each window, are modelled using the sea and land sample spaces obtained by the altitude information which has very low resolution compared to the image. These models...
Hypothesis based detection of building with rectilinear projection in satellite images using shade and color information
Güdücü, Volkan; Halıcı, Uğur (2010-12-01)
A new hypothesis based method for detecting rectilinear buildings, that have ground projection made of combination of rectangles, in satellite images is proposed. While the hypotheses are established using the lines detected in the satellite images they are verified by using shadow and color segmentation information. The proposed method is implemented in MATLAB and tested in satellite images of different urban areas. The experimental results obtained are encouraging. ©2010 IEEE.
Unsupervised Change Detection in Satellite Images using Oversegmentation and Mutual Information
Taskesen, Bahar; Besbinar, Beril; Koz, Alper; Alatan, Abdullah Aydın (2017-05-18)
In this paper, a novel solution to the problem of unsupervised change detection in bitemporal satellite images is presented. Information measures, which are well-known and commonly-used in the change detection literature, result in unsharp change maps and masks without well defined boundaries as a result of local computation. In the proposed method, mutual information with local joint distributions computed within the over-segments after image registration, radiometric correction and some preprocessing step...
Citation Formats
A. O. Ok, C. Senaras, and B. Yuksel, “Automated Detection of Arbitrarily Shaped Buildings in Complex Environments From Monocular VHR Optical Satellite Imagery,” IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, pp. 1701–1717, 2013, Accessed: 00, 2020. [Online]. Available: