Road extraction from satellite images by self supervised classification and perceptual grouping

Download

index.pdf

Date

2013

Author

Şahin, Eda

Metadata

Show full item record

Item Usage Stats

178
views

129
downloads

Road network extraction from high resolution satellite imagery is the most frequently utilized technique for updating and correcting geographic information system (GIS) databases, registering multi-temporal images for change detection and automatically aligning spatial datasets. This advance method is widely employed due to the improvements in satellite technology such as development of new sensors for high resolution imagery. To avoid the cost of the human interaction, various automatic and semi-automatic road extraction methods are developed and proposed in the literature. The aim of this study is to develop a fully automatized method which can extract road networks by using the spectral and structural features of the roads. In order to achieve this goal we set various objectives and work them out one by one. First bjective is to obtain reliable road seeds, since they are crucial for determining road regions correctly in the classification step. Second objective is finding most onvenient features and classification method for the road extraction. The third objective is to locate road centerlines which are defines the road topology. A number of algorithms are developed and tested throughout the thesis to achieve these objectives and the advantages of the proposed ones are explained. The final version of the proposed algorithm is tested by three band (RGB) satellite images and the results are compared with other studies in the literature to illustrate the benefits of the proposed algorithm.

Subject Keywords

Remote-sensing images., Roads, Geographical perception., Gaussian processes.

URI

http://etd.lib.metu.edu.tr/upload/12615351/index.pdf
https://hdl.handle.net/11511/22414

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Airplane Localization in Satellite Images by using Visual Attention Ozyer, Gulsah Tumuklu; Yarman Vural, Fatoş Tunay (2013-04-26) Automatic target detection from the satellite images is an important tool for various applications including mapping, city planning and defense industry. In this paper, we propose a new two-stage method to identify the airplane regions in the airport images by using visual attention. In the first stage, the interesting patches in the image is aimed to extract from the high resolution images. For that purpose, Itti-Koch visual attention model which is inspired from human vision system is used. In the second ...
URBAN BUILDING DETECTION FROM OPTICAL AND INSAR FEATURES EXPLOITING CONTEXT Wegner, J. D.; Ok, Ahmet; Thiele, A.; Rottensteiner, F.; Soergel, U. (2010-09-03) We investigate the potential of combined features of aerial images and high-resolution interferometric SAR (InSAR) data for building detection in urban areas. It is shown that completeness and correctness may be increased if we integrate both InSAR double-bounce lines and 3D lines of stereo data in addition to building hints of a single optical orthophoto. In order to exploit context information, which is crucial for object detection in urban areas, we use a Conditional Random Field approach. It proves to b...
Association rule mining using fuzzy spatial data cubes Isik, Narin; Yazıcı, Adnan (2006-07-01) The popularity of spatial databases increases since the amount of the spatial data that need to be handled has increased by the use of digital maps, images from satellites, video cameras, medical equipment, sensor networks, etc. Spatial data are difficult to examine and extract interesting knowledge; hence, applications that assist decision-making about spatial data like weather forecasting, traffic supervision, mobile communication, etc. have been introduced. In this thesis, more natural and precise knowle...
Geographic information system-based visualization system for planning and monitoring of repetitive construction projects Sönmez, Rifat (Canadian Science Publishing, 2008-11-01) This study presents a visualization system based on a geographic information system (GIS) for planning and monitoring the progress of construction projects that are repetitive due to their geometrical layout. A prototype system was developed and applied to an actual pipeline project to demonstrate the advantages of the proposed approach. The primary advantage of the system is improved visualization of geographical conditions and their impact on the progress rate. Enhanced visual representation of the schedu...
Analysis of near-field ultra-wideband radar imaging algorithms Arabacı, Ahmet; Koç, Seyit Sencer; Department of Electrical and Electronics Engineering (2017) Recently, near-field ultra-wideband radar imaging algorithms have an important place in short range imaging applications by providing high resolution in both range and cross-range. In this study, the near-field ultra-wideband radar imaging algorithms in the literature such as Holographic Image Reconstruction Algorithm, Range Migration Algorithm, MIMO Based Range Migration Algorithm and MIMO Based Kirchhoff Migration Algorithm have been implemented using MATLAB. The algorithms are applied to modeled transmit...

Citation Formats

E. Şahin, “Road extraction from satellite images by self supervised classification and perceptual grouping,” M.S. - Master of Science, Middle East Technical University, 2013.