Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Comparison Of Different Aproaches To Extract Heterogeneous Objects From An Image Using An Orchards Example, Przemysław Kupidura, Gwadera Łukasz
Comparison Of Different Aproaches To Extract Heterogeneous Objects From An Image Using An Orchards Example, Przemysław Kupidura, Gwadera Łukasz
Przemysław Kupidura
Traditional, pixel-based classification is very often an useless tool for an automatic extraction of heterogeneous types of land cover. This paper presents the application of mathematical morphology for a semi-automatic extraction of heterogenous objects using an example of orchards. Thanks to this algorithm it is possible to obtain orchards pixels of unique set of digital numbers, allowing succesful application of a traditional pixel-based classification for extraction of this class.The algorithm concerning a sequence of morphological operations of multispectral satellite images of very high resolution (VHR) is then veryfied on test images. The paper concerns also a comparison of an efficiency …
Semi-Automatic Method For A Built-Up Area Intensity Survey Using Morphological Granulometry, Przemysław Kupidura
Semi-Automatic Method For A Built-Up Area Intensity Survey Using Morphological Granulometry, Przemysław Kupidura
Przemysław Kupidura
Built-up areas as a land-use type are easy to extract in a visual photo-interpretation process, however their heterogeneous character makes theirs automatic or semi-automatic extraction very complicated, even impossible using non-contextual, pixel-based methods of image classification. This paper concerns the application of the semi-automatic method of the extraction of built-up areas in satellite images. Granulometric maps, a mathematical morphology operator is used as a main tool for surveying a heterogeneity of particular parts of an aerial or satellite image. This function measures amount and size of objects in the determined neighborhood of each pixel of an image. Pixels representing built-up …