2013
DOI: 10.5194/isprsannals-ii-3-w3-79-2013
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Abstract: ABSTRACT:This paper presents an original unsupervised framework to identify regions belonging to buildings and roads from monocular very high resolution (VHR) satellite images. The proposed framework consists of three main stages. In the first stage, we extract information only related to building regions using shadow evidence and probabilistic fuzzy landscapes. Firstly, the shadow areas cast by building objects are detected and the directional spatial relationship between buildings and their shadows is modell… Show more

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Cited by 8 publications
(9 citation statements)
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References 38 publications
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“…Table II shows the pixel-level vegetation classification results. It can be seen that the proposed method clearly obtains better accuracy which outperforms the methods in [5], [6] by up to 2%-12%. It is also noted that the proposed method is more reliable and stable which gives consistently good performance above 97% for each image.…”
Section: Image Pixel-level Vegetation Classification Resultsmentioning
confidence: 83%
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“…Table II shows the pixel-level vegetation classification results. It can be seen that the proposed method clearly obtains better accuracy which outperforms the methods in [5], [6] by up to 2%-12%. It is also noted that the proposed method is more reliable and stable which gives consistently good performance above 97% for each image.…”
Section: Image Pixel-level Vegetation Classification Resultsmentioning
confidence: 83%
“…In order to improve the classification accuracy, shadow detection and removal will be explored for vegetation detection in the future work. Ground truth (c) Proposed method (d) Methods in [5], [6]. White pixels indicating the vegetation areas, and dark pixels indicating the non-vegetation areas.…”
Section: B Image Patch-level Vegetation Detection Resultsmentioning
confidence: 99%
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“…Furthermore, because shadows cover a considerable portion of an image, they play a supporting role on automated analysis. In this context, the shadow presence in single VHR multispectral images has been exploited as strong evidence of the existence of a different building structure, such as buildings detection (Ok, 2013a), arbitrarily shaped buildings in complex environments (Ok et al, 2013), the extraction of above ground circular structures (Ok, 2014), and automated extraction of buildings and roads (Ok, 2013b). Shadows are an important cue for information not only about man-made structures but also about supporting urban sustainability.…”
Section: The Importance Of Shadow Detection In Urban Environmentsmentioning
confidence: 99%