Specifically, for the former problem, we apply multiple features (spectral feature, spatial feature and gradient feature) to obtain not only the spectral ...
Abstract: Accurate road extraction from complex backgrounds plays a fundamental role in a wide range of remote sensing applications.
To address these two problems, we propose a novel approach via adaptive graph cuts with multiple features. Specifically, for the former problem, we apply ...
Specifically, for the former problem, we apply multiple features (spectral feature, spatial feature and gradient feature) to obtain not only the spectral ...
In this paper, we propose a graph cuts (GC) based probability propagation approach to automatically extract road network from complex remote sensing images.
This paper attempts to provide a comprehensive survey on road extraction methods that use 2D earth observing images and 3D LiDAR point clouds.
This paper presents a GPU implementation of normalized cuts for road extraction problem using panchro- matic satellite imagery. The roads have been ...
Aug 15, 2021 · This article provides a detailed review of the studies on road feature extraction from raster maps, which helps to gain a thorough understanding of the ...
ABSTRACT. In this paper, we propose a graph cuts (GC) based probability propagation approach to automatically extract road network.
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Oct 13, 2022 · This paper proposes a land cover background-adaptive framework for large-scale road extraction. Method: A large number of sample image blocks (6820) are ...