Abstract
In this paper, a novel technique is presented to detect buildings from very high resolution satellite image. This work builds on the learning of ICA based building detection technique from the very high resolution (VHR) multispectral satellite images presented in [1]. The candidate building pixels obtained through ICA are used to extract maximally stable extremal regions (MSER) which are then filtered using geometric properties to obtain final potential buildings. The technique is aimed at reducing false detection at pixel-level and improving object-level performance of [1]. Combining the two works offers an unsupervised building detection technique which is robust towards size, shape, color, types of rooftops and shadows. A wider test image set consisting of 15 images of different dimensions are used to evaluate performance of the complete detection process. The combined technique achieves object-level precision and recall of 80.64% and 83.65% respectively.
Published Version
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