Share Email Print
cover

Journal of Applied Remote Sensing

Automatic change detection in remote sensing images using level set method with neighborhood constraints
Author(s): Guo Cao; Yazhou Liu; Yanfeng Shang
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

An automatic change detection (CD) method based on level set evolution in remote sensing images is proposed. The CD problem is formulated as a segmentation issue to discriminate the changed class from the unchanged class in the difference images. The strategy of the level set initialization is considered and neighborhood constraints are added to the level set energy model. In addition, a coarse-to-fine procedure is adopted. A chief advantage of our approach is to be able to obtain correct results even when the difference image contains different types of changes. Furthermore, the proposed method is robust against noise and yields smooth boundaries of changed regions without manual parameter adjustment. We implement the proposed method in a multiresolution framework and validate the algorithm systematically with a variety of remote sensing images by low- as well as high-spatial resolution sensors, including Landsat-5 TM, SPOT5, IKONOS, etc.

Paper Details

Date Published: 14 February 2014
PDF: 15 pages
J. Appl. Remote Sens. 8(1) 083678 doi: 10.1117/1.JRS.8.083678
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Guo Cao, Nanjing Univ. of Science and Technology (China)
Yazhou Liu, Nanjing Univ. of Science and Technology (China)
Yanfeng Shang, Third Research Institute of Ministry of Public Security (China)


© SPIE. Terms of Use
Back to Top