knowledge based fusion of high resolution radar and optical images for road extraction in urban areas
Authors
abstract
in this article, a new method for fusion of high resolution optical and radar data for higher quality road extraction is presented. the proposed methodology consists of two stages of separate road detection from each data and knowledge based fusion of results. neural networks are separately applied on high resolution ikonos and terrasar-x images for road detection, using a variety of texture parameters. then knowledge based fusion using some thresholds about gray level of narrow roads and vegetation is done. accuracy assessment parameters were evaluated and 79.42% for rcc, 93.51% for bcc and 0.27 for the parameter rmse obtained. the obtained results shows the efficiency of the proposed method.
similar resources
Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images
As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...
full textHigh Resolution Radar Imaging of Urban Areas
New synthetic aperture radar (SAR) sensors on satellites like TerrsSAR-X allow flexible mapping with a large coverage or a high resolution of about one meter. Leading-edge airborne SAR sensors provide spatial resolutions on the order of a decimetre. In such data, many features of urban objects can be identified, which were beyond the scope of radar remote sensing before. But, SAR images are oft...
full textAutomatic road extraction from high-resolution images applied over urban areas
Road extraction plays an important role in many applications such as car navigation. However, the manual extraction of roads is a laborious and tedious task. Road extraction from satellite images has drawn considerable attention in last years due to the recent availability of commercial high-resolution optical satellite imagery. Road extraction strategies are usually classified into two categor...
full textVery High Resolution Land Cover Extraction in Urban Areas: Very High Resolution Urban Land Cover Extraction Using Airborne Hyperspectral Images
During last decade, needs for high resolution land cover data have been growing. Such knowledge is namely often required in environment monitoring studies. Thus, to answer these needs, national mapping or environment agencies, in many countries, have undertaken the production of such large scale national land cover database. Nevertheless, these databases provide a general classification and may...
full textA New Method for Urban Road Extraction based on High Resolution Remote Sensing Images
An efficient method to extract urban road based on the side trees from a high resolution remote sensing image is proposed. First, the high resolution remote sensing image was preprocessed so as to improve the extraction accuracy and reduce the difficulty of later treatment. Second, according to the reflective property of side trees and urban road, it is necessary to detect the side trees region...
full textRoad Extraction from High Resolution Satellite Images
Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this paper, the road extraction approach is based on Active Contour Models for 1-meter resolution g...
full textMy Resources
Save resource for easier access later
Journal title:
رادارجلد ۱، شماره ۱، صفحات ۰-۰
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023