TY - JOUR
T1 - Use of colour transformation and the geodesic method for road centreline extraction from VHR satellite images
AU - Miao, Zelang
AU - Gao, Lipeng
AU - He, Yueguang
AU - Wu, Lixin
AU - Shi, Wenzhong
AU - Samat, Alim
AU - Liu, Sicong
AU - Li, Jia
PY - 2019/5/19
Y1 - 2019/5/19
N2 - Seed point-based road extraction methods are vital for extracting road networks from satellite images. Despite its effectiveness, roads in very high-resolution (VHR) satellite images are complicated, such as road occlusion and material change. To tackle this issue, this paper proposes to use the colour space transformation and geodesic method. First, the test image is converted from Red-Green-Blue colour space to Hue-Saturation-Value colour space to reduce the material change influence. The geodesic method is subsequently applied to extract initial road segments that link road seed points provided by users. At last, the initial result is adjusted by a kernel density estimation method to produce centred roads. The presented method is quantitatively evaluated on three test images. Experiments show that the proposed method yields a substantial improvement over cutting-edge technologies. The findings in this study shine new light on a practical solution for road extraction from satellite images.
AB - Seed point-based road extraction methods are vital for extracting road networks from satellite images. Despite its effectiveness, roads in very high-resolution (VHR) satellite images are complicated, such as road occlusion and material change. To tackle this issue, this paper proposes to use the colour space transformation and geodesic method. First, the test image is converted from Red-Green-Blue colour space to Hue-Saturation-Value colour space to reduce the material change influence. The geodesic method is subsequently applied to extract initial road segments that link road seed points provided by users. At last, the initial result is adjusted by a kernel density estimation method to produce centred roads. The presented method is quantitatively evaluated on three test images. Experiments show that the proposed method yields a substantial improvement over cutting-edge technologies. The findings in this study shine new light on a practical solution for road extraction from satellite images.
UR - http://www.scopus.com/inward/record.url?scp=85059584397&partnerID=8YFLogxK
U2 - 10.1080/01431161.2018.1558374
DO - 10.1080/01431161.2018.1558374
M3 - Journal article
AN - SCOPUS:85059584397
SN - 0143-1161
VL - 40
SP - 4043
EP - 4058
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 10
ER -