Topological Space Knowledge Distillation for Compact Road Extraction in Optical Remote Sensing Images

Application Of High-Resolution Remote Sensing Images In Road Extraction

knowledge based fusion of high resolution radar and optical images for road extraction in urban areas

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 pa...

Markov Random Field for Road Extraction Applications in Remote Sensing Images

Bayesian methods coupled with Markovian frameworks has several applications in remote sensing images processing, such as the pixel level applications like filtering, segmentation and classification, and the higher level applications like object recognition and organization etc. This article illustrates the powerfulness of Markovian model at two levels for the road extraction problem in remote s...

A 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...

Segmentation of optical remote sensing images for detecting homogeneous regions in space and time

With the amount of multitemporal and multiresolution images growing exponentially, the number of image segmentation applications is recently increasing and, simultaneously, new challenges arise. Hence, there is a need to explore new segmentation concepts and techniques that make use of the temporal dimension. This paper describes a spatio-temporal segmentation that adapts the traditional region...