Road Centreline Extraction of High-Resolution Remote Sensing Image with Improved Beamlet Transform and K-Means Clustering
- 16 February 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Arabian Journal for Science and Engineering
- Vol. 46 (4), 4153-4162
- https://doi.org/10.1007/s13369-021-05412-1
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (41701537)
- CAS Strategic Priority Research Program (XDA19030402)
This publication has 27 references indexed in Scilit:
- Junction‐aware water flow approach for urban road network extractionIET Image Processing, 2016
- Region-based urban road extraction from VHR satellite images using Binary Partition TreeInternational Journal of Applied Earth Observation and Geoinformation, 2016
- Target detection for SAR images based on beamlet transformMultimedia Tools and Applications, 2014
- Assessment of thermoacoustic instabilities in a partially premixed model combustor using URANS approachApplied Thermal Engineering, 2014
- An Integrated Method for Urban Main-Road Centerline Extraction From Optical Remotely Sensed ImageryIEEE Transactions on Geoscience and Remote Sensing, 2013
- Delineation and geometric modeling of road networksISPRS Journal of Photogrammetry and Remote Sensing, 2010
- Region-based perceptual grouping for road extraction from high-resolution imagesInternational Journal of Intelligent Systems Technologies and Applications, 2010
- GENETIC ALGORITHM SOLUTION FOR MULTI-PERIOD TWO-ECHELON INTEGRATED COMPETITIVE/UNCOMPETITIVE FACILITY LOCATION PROBLEMAsia-Pacific Journal of Operational Research, 2008
- Quantitative modeling of suspended sediment in middle Changjiang River from modisChinese Geographical Science, 2006
- Beamlets and Multiscale Image AnalysisLecture Notes in Computational Science and Engineering, 2002