Urban Road Extraction High resolution remotely sensed imagery with Gabor texture and geometrical Features

  • Hualong Hu Information Engineering University
  • Bing Wu Institute, General Staff ,PLA
  • Shaomei Huang 61287 troops
Ariticle ID: 3466
49 Views, 0 PDF Downloads
Keywords: Road extraction, Gabor filter, texture, Geometrical features, Mathematical morphology

Abstract

Through the feature analysis of the frequency curve , The paper proposed a new method which integrated Gabor texture and geometrical features in the urban road Ction from high resolution remotely sensed imagery. in the experiment, the texture features in different frequencies and Different directions were obtained by a given bank of Gabor filters,andthen K-means clus Tering method is applied for imagery segmentation. The morphological methods were utilized to separate the road objects from Non-^oadobjects,and the geometrical features were applied to take out the non-road. Then the extracted roads were regulated by mathematical morphology. The result showed this proposed method could effectively extract the urban road information from high resolution Remo Tely sensed imagery.

References

1. CHRISTOPHE E, Inglada J. Robust Road

extraction for

High resolution satellite image [C] ^proceedingsthe

IEEE International conference on image

processing. San Antonio, 2007:437-440.

2. jialing , Zhao L , Zhang Jianhui , , and so on . Is

based on the Landsat etm+ Image City

Road Information extraction Research J]. Remote

sensing technology and Applications , ???? , (5):

478-482.

3. GAMBA P, DELL ACQUA F, Lisini G.

Improving Urban Road extraction in high

resolution Images EXP loiting directional

filtering, perceptual Grouping and simple

topologicalconcepts[ J]. IEEE Geoscience

andRemote Sensing Letters, 2006,3 (3) :387-

391.

4. Shingwen , Ding . based on multiple

seed point fuzzy connectivity SPOT

Image Path extract all Journal of

Surveying and Mapping science and

technology , 2009,26 (3): 190494.

5. Zhou Jiachang, , Zhou An Send, Tau ,

etc . A high-resolution remote sensing

image Urban Road net Fetch method

JJ. Journal of South Central

University : Natural Science Edition ,

2013,6 : 2385-2391.

6. Xu Rui. . a method for extracting urban roads

from remote sensing images combining shape

and homogeneity

J. Journal of Surveying and Mapping science and

technology , 2014,31 (1) : 53-56.

7. Wang kun couldn't, Wan Chuan, Cuiling .

fusion of high-resolution remote sensing of

texture and shape features Image Path

Extraction J. Remote Sensing information ,

(5) :741.

8. Hu Haixu, Wang, He Houjun. . high score based

on texture features and mathematical

morphology resolution image City Road

extraction J. Geography and Geographic

information Science , 2008,24 (6) :46-49.

9. Huanhuan , Zhu Heng, Wang Ruiyan. .

application of texture and geometry features in

road extraction

J. Computer and modernization , (7) : å±® 9.

10. Wang Ke , Xiaopeng , Feng Xuezhi , , and so on .

High resolution remote sensing map based on

frequency domain filtering extracting

information like City watercourses J. Journal of

Remote Sensing , 2013,17 (2): 269485.

11. Zhao , Feng Xuezhi , Xiaopeng . Remote

sensing image based on frequency domain

feature City Road Road green space Cover

outline extraction J. Remote Sensing

information , 2014,29 (3): 50-56.

12. Huangqiuyan , Xiaopeng , Feng Xuezhi , , and

so on . a Is based on Tvgabor high of the model

Resolution Remote sensing image farmland

information extraction method J. Remote

Sensing information , 2014,29 (2) :79-84.

13. Conners R W, HARLOW CA. A theoretical

Comparison of texture algorithms J. IEEE

Transactions on pattern analysis and

Machine Intelligence, 1980 (3): 204-222.

14. kamarainenjk, Kyrkiv, Kalviainenh.

invariance Properties of Gabor Filter

Based Features-overview and

application J]. IEEE transactions on

Image Processing, 2006 (5): 1088-4099.

15. manjunath B, MA W. Texture Feature for

browsing and retrieval of the Image Data J.

IEEE Transactions on pattern analysis and

Machine Intelligence, 1996,18 (8): 837-842.

16. Wang Pei, Feng Xuezhi, Xiaopeng , etc .

for remote sensing image texture

extraction Ga-bor Filter Group parameter

solution Research J. Remote Sensing

information , 2008 (6): 5 Seven .

17. JAIN A K, Farrokhniaf. Unsupervised texture

segmentation Using Gabor Filters J]. Pattern

Recognition, 1991 (): 1167-1186.

18. Huang . High resolution remote sensing

image Multiscale texture , shape feature

extraction and facing Object Category

Research [D]. Wuhan : Wuhan University ,

2009:23.

19. Tri Yu. . image processing and parsing one by

one Mathematical Morphology method and

application [M]. North Beijing : Science

Press , 2000:43-51.

20. ZHANG J G, TAN T N, MA L. Invariant

Texture Segmentation Via circular Gabor

Filter [C] // Proceedings of the 16th iapr

International Conference on pattern

Recognition (IC PR). Quebec, Canada,

2002:901-904.

Published
2024-02-27
How to Cite
Hu, H., Wu, B., & Huang, S. (2024). Urban Road Extraction High resolution remotely sensed imagery with Gabor texture and geometrical Features. Remote Sensing, 13(1). https://doi.org/10.18282/rs.v13i1.3466
Section
Original Research Articles