Standardization of evaluation techniques for building extraction is an unresolved issue in the fields of remote sensing, photogrammetry, and computer vision. In this paper, we propose a metric with a working title 'PoLiS metric' to compare two polygons. The PoLiS metric is a positive definite and symmetric function that satisfies a triangle inequality. It accounts for shape and accuracy differences between the polygons, is straightforward to apply, and requires no thresholds. We show through an example that the PoLiS metric between two polygons changes approximately linearly with respect to small translation, rotation, and scale changes. Furthermore, we compare building polygons extracted from a digital surface model to the reference building polygons by computing PoLiS, Hausdorff and Chamfer distances. The results show that quantification by PoLiS distance of dissimilarity between polygons is consistent with visual perception. What is more, Hausdorff and Chamfer distances overrate the dissimilarity when one polygon has more vertices than the other. We propose an approach towards standardizing building extraction evaluation, which may also have broader applications in the field of shape similarity.
ABSTRACT:Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels. Spectral unmixing methods can be employed to estimate the fractions of reflected light from the different objects within the pixel area. However, spectral unmixing does not provide any spatial information about the sources and therefore additional information is needed to precisely locate the sources. In order to restore the spatial information of hyperspectral images we propose a hyperspectral and multispectral image fusion method based on spectral unmixing. The algorithm is tested with HyMAP image data consisting of 125 spectral bands and a simulated multispectral image consisting of 8 bands.
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