Abstract
Abstract. Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar) imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR) airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM), followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve active contour model (snakes). The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.
Highlights
1.1 MotivationThe research on the use of aerial photography to generate cartographic products has intensified in recent decades
The main purpose of this paper is to present a solution that enables the extraction of roads present in airborne radar images of high resolution
This work presented the use of Self-Organizing Maps as a semiautomatic seeding roads approach in an airborne synthetic aperture radar (SAR) image
Summary
The research on the use of aerial photography to generate cartographic products has intensified in recent decades. Applications such as the collection of altimetry in certain regions or updating maps the location of roads, buildings or other targets are examples of acquisitions by remote sensing. The formation of images is usually performed by optical or radar sensors (Radio Detection and Ranging), on aircraft or satellites platforms, called airborne and orbital images, respectively. The images are acquired by radiation emitted by the sensors, where part of the energy is absorbed by the object, part is lost, and the rest is backscattered. The energy backscattered returns to the sensor which performs the reading
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