Change detection using l0 smoothing and superpixel techniques

Xiaoliang Shi; Yingying Xu; Guixu Zhang; Chaomin Shen

doi:10.1007/978-3-319-25159-2_54

Change detection using l₀ smoothing and superpixel techniques

Xiaoliang Shi, Yingying Xu, Guixu Zhang, Chaomin Shen^*

^*Corresponding author for this work

School of Computer Science and Technology

East China Normal University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We propose an unsupervised change detection method for satellite images using L₀ smoothing, superpixel techniques and k-means. First, we produce the difference image according to image types (synthetic aperture radar or optical images). Second, we use L₀ smoothing, an image editing method that can simultaneously sharpen major edges and smooth low-amplitude structures, to generate two difference images with distinct smooth levels. Third, k-means algorithm with k = 2 is applied on one smoothed difference image to cluster all pixels into changed or unchanged classes. Fourth, the Voronoi-Cells (VCells) algorithm is applied on the other difference image to obtain roughly uniform superpixels while preserving local image boundaries. Finally, we calculate the change degree for each superpixel, and the change detection map is produced by using k-means again. The novelties of this paper are that we use the L₀ smoothing to reduce noise and preserve edges, and utilize the spatial information with the help of superpixel. Experimental results on synthetic aperture radar and optical images show the effectiveness of our approach.

Original language	English
Title of host publication	Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings
Editors	Zili Zhang, Songmao Zhang, Zili Zhang, Martin Wirsing, Martin Wirsing, Martin Wirsing, Zili Zhang, Songmao Zhang, Songmao Zhang
Publisher	Springer Verlag
Pages	600-611
Number of pages	12
ISBN (Print)	9783319251585, 9783319251585, 9783319251585
DOIs	https://doi.org/10.1007/978-3-319-25159-2_54
State	Published - 2015
Event	8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 - Chongqing, China Duration: 28 Oct 2015 → 30 Oct 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9403
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015
Country/Territory	China
City	Chongqing
Period	28/10/15 → 30/10/15

Keywords

Change detection
L smoothing
Superpixel

Access to Document

10.1007/978-3-319-25159-2_54

Cite this

Shi, X., Xu, Y., Zhang, G., & Shen, C. (2015). Change detection using l₀ smoothing and superpixel techniques. In Z. Zhang, S. Zhang, Z. Zhang, M. Wirsing, M. Wirsing, M. Wirsing, Z. Zhang, S. Zhang, & S. Zhang (Eds.), Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings (pp. 600-611). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9403). Springer Verlag. https://doi.org/10.1007/978-3-319-25159-2_54

Shi, Xiaoliang ; Xu, Yingying ; Zhang, Guixu et al. / Change detection using l₀ smoothing and superpixel techniques. Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. editor / Zili Zhang ; Songmao Zhang ; Zili Zhang ; Martin Wirsing ; Martin Wirsing ; Martin Wirsing ; Zili Zhang ; Songmao Zhang ; Songmao Zhang. Springer Verlag, 2015. pp. 600-611 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{22b464edd13948e2a779dd48a5ff9e36,

title = "Change detection using l0 smoothing and superpixel techniques",

abstract = "We propose an unsupervised change detection method for satellite images using L0 smoothing, superpixel techniques and k-means. First, we produce the difference image according to image types (synthetic aperture radar or optical images). Second, we use L0 smoothing, an image editing method that can simultaneously sharpen major edges and smooth low-amplitude structures, to generate two difference images with distinct smooth levels. Third, k-means algorithm with k = 2 is applied on one smoothed difference image to cluster all pixels into changed or unchanged classes. Fourth, the Voronoi-Cells (VCells) algorithm is applied on the other difference image to obtain roughly uniform superpixels while preserving local image boundaries. Finally, we calculate the change degree for each superpixel, and the change detection map is produced by using k-means again. The novelties of this paper are that we use the L0 smoothing to reduce noise and preserve edges, and utilize the spatial information with the help of superpixel. Experimental results on synthetic aperture radar and optical images show the effectiveness of our approach.",

keywords = "Change detection, L smoothing, Superpixel",

author = "Xiaoliang Shi and Yingying Xu and Guixu Zhang and Chaomin Shen",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 ; Conference date: 28-10-2015 Through 30-10-2015",

year = "2015",

doi = "10.1007/978-3-319-25159-2\_54",

language = "英语",

isbn = "9783319251585",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "600--611",

editor = "Zili Zhang and Songmao Zhang and Zili Zhang and Martin Wirsing and Martin Wirsing and Martin Wirsing and Zili Zhang and Songmao Zhang and Songmao Zhang",

booktitle = "Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings",

address = "德国",

}

Shi, X, Xu, Y, Zhang, G & Shen, C 2015, Change detection using l₀ smoothing and superpixel techniques. in Z Zhang, S Zhang, Z Zhang, M Wirsing, M Wirsing, M Wirsing, Z Zhang, S Zhang & S Zhang (eds), Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9403, Springer Verlag, pp. 600-611, 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015, Chongqing, China, 28/10/15. https://doi.org/10.1007/978-3-319-25159-2_54

Change detection using l₀ smoothing and superpixel techniques. / Shi, Xiaoliang; Xu, Yingying; Zhang, Guixu et al.
Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. ed. / Zili Zhang; Songmao Zhang; Zili Zhang; Martin Wirsing; Martin Wirsing; Martin Wirsing; Zili Zhang; Songmao Zhang; Songmao Zhang. Springer Verlag, 2015. p. 600-611 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9403).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Change detection using l0 smoothing and superpixel techniques

AU - Shi, Xiaoliang

AU - Xu, Yingying

AU - Zhang, Guixu

AU - Shen, Chaomin

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - We propose an unsupervised change detection method for satellite images using L0 smoothing, superpixel techniques and k-means. First, we produce the difference image according to image types (synthetic aperture radar or optical images). Second, we use L0 smoothing, an image editing method that can simultaneously sharpen major edges and smooth low-amplitude structures, to generate two difference images with distinct smooth levels. Third, k-means algorithm with k = 2 is applied on one smoothed difference image to cluster all pixels into changed or unchanged classes. Fourth, the Voronoi-Cells (VCells) algorithm is applied on the other difference image to obtain roughly uniform superpixels while preserving local image boundaries. Finally, we calculate the change degree for each superpixel, and the change detection map is produced by using k-means again. The novelties of this paper are that we use the L0 smoothing to reduce noise and preserve edges, and utilize the spatial information with the help of superpixel. Experimental results on synthetic aperture radar and optical images show the effectiveness of our approach.

AB - We propose an unsupervised change detection method for satellite images using L0 smoothing, superpixel techniques and k-means. First, we produce the difference image according to image types (synthetic aperture radar or optical images). Second, we use L0 smoothing, an image editing method that can simultaneously sharpen major edges and smooth low-amplitude structures, to generate two difference images with distinct smooth levels. Third, k-means algorithm with k = 2 is applied on one smoothed difference image to cluster all pixels into changed or unchanged classes. Fourth, the Voronoi-Cells (VCells) algorithm is applied on the other difference image to obtain roughly uniform superpixels while preserving local image boundaries. Finally, we calculate the change degree for each superpixel, and the change detection map is produced by using k-means again. The novelties of this paper are that we use the L0 smoothing to reduce noise and preserve edges, and utilize the spatial information with the help of superpixel. Experimental results on synthetic aperture radar and optical images show the effectiveness of our approach.

KW - Change detection

KW - L smoothing

KW - Superpixel

UR - https://www.scopus.com/pages/publications/84951832336

U2 - 10.1007/978-3-319-25159-2_54

DO - 10.1007/978-3-319-25159-2_54

M3 - 会议稿件

AN - SCOPUS:84951832336

SN - 9783319251585

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 600

EP - 611

BT - Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings

A2 - Zhang, Zili

A2 - Zhang, Songmao

A2 - Zhang, Zili

A2 - Wirsing, Martin

A2 - Zhang, Zili

A2 - Zhang, Songmao

PB - Springer Verlag

T2 - 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015

Y2 - 28 October 2015 through 30 October 2015

ER -

Shi X, Xu Y, Zhang G, Shen C. Change detection using l₀ smoothing and superpixel techniques. In Zhang Z, Zhang S, Zhang Z, Wirsing M, Wirsing M, Wirsing M, Zhang Z, Zhang S, Zhang S, editors, Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. Springer Verlag. 2015. p. 600-611. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-25159-2_54

Change detection using l₀ smoothing and superpixel techniques

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this