Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities

S. Valero; C. Pelletier; M. Bertolino

doi:10.1109/IGARSS.2016.7729596

Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities

S. Valero
, C. Pelletier
, M. Bertolino

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

7 Citations (Scopus)

Abstract

The reconstruction of missing data in image time series due to cloud masking, among other reasons, is addressed in this paper. A new patch-based strategy based on the similarities between the spatial, spectral and temporal evolutions of the image pixel values is proposed. Experiments are carried out using Landsat-8 and SPOT-5 image time series. The proposed methodology is compared to classical temporal interpolation approaches.

Original language	English
Title of host publication	2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings
Subtitle of host publication	July 10–15, 2016 Beijing, China
Editors	Jiancheng Shi, Huadong Guo, Kun-shan Chen
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	2308-2311
Number of pages	4
ISBN (Electronic)	9781509033324
ISBN (Print)	9781509033331
DOIs	https://doi.org/10.1109/IGARSS.2016.7729596
Publication status	Published - 1 Nov 2016
Externally published	Yes
Event	IEEE International Geoscience and Remote Sensing Symposium 2015 - Fiera Milano Congressi - Milan Convention Center, Milan, Italy Duration: 26 Jul 2015 → 31 Jul 2015 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7303999 (IEEE Conference Proceedings)

Conference

Conference	IEEE International Geoscience and Remote Sensing Symposium 2015
Abbreviated title	IGARSS 2015
Country/Territory	Italy
City	Milan
Period	26/07/15 → 31/07/15
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7303999 (IEEE Conference Proceedings)

Keywords

Cloud removal
High resolution
image reconstruction
Satellite Image Time Series

Access to Document

10.1109/IGARSS.2016.7729596

Cite this

Valero, S., Pelletier, C., & Bertolino, M. (2016). Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. In J. Shi, H. Guo, & K. Chen (Eds.), 2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China (pp. 2308-2311). Article 7729596 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IGARSS.2016.7729596

Valero, S. ; Pelletier, C. ; Bertolino, M. / Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. 2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China. editor / Jiancheng Shi ; Huadong Guo ; Kun-shan Chen. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2016. pp. 2308-2311

@inproceedings{867aca8ece3045d383518f8a3de91cac,

title = "Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities",

abstract = "The reconstruction of missing data in image time series due to cloud masking, among other reasons, is addressed in this paper. A new patch-based strategy based on the similarities between the spatial, spectral and temporal evolutions of the image pixel values is proposed. Experiments are carried out using Landsat-8 and SPOT-5 image time series. The proposed methodology is compared to classical temporal interpolation approaches.",

keywords = "Cloud removal, High resolution, image reconstruction, Satellite Image Time Series",

author = "S. Valero and C. Pelletier and M. Bertolino",

year = "2016",

month = nov,

day = "1",

doi = "10.1109/IGARSS.2016.7729596",

language = "English",

isbn = "9781509033331",

pages = "2308--2311",

editor = "Jiancheng Shi and Guo, \{Huadong \} and Chen, \{Kun-shan \}",

booktitle = "2016 IEEE International Geoscience \& Remote Sensing Symposium - Proceedings",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE International Geoscience and Remote Sensing Symposium 2015, IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",

url = "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7303999",

}

Valero, S, Pelletier, C & Bertolino, M 2016, Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. in J Shi, H Guo & K Chen (eds), 2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China., 7729596, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 2308-2311, IEEE International Geoscience and Remote Sensing Symposium 2015, Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2016.7729596

Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. / Valero, S.; Pelletier, C.; Bertolino, M.
2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China. ed. / Jiancheng Shi; Huadong Guo; Kun-shan Chen. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 2308-2311 7729596.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

TY - GEN

T1 - Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities

AU - Valero, S.

AU - Pelletier, C.

AU - Bertolino, M.

PY - 2016/11/1

Y1 - 2016/11/1

N2 - The reconstruction of missing data in image time series due to cloud masking, among other reasons, is addressed in this paper. A new patch-based strategy based on the similarities between the spatial, spectral and temporal evolutions of the image pixel values is proposed. Experiments are carried out using Landsat-8 and SPOT-5 image time series. The proposed methodology is compared to classical temporal interpolation approaches.

AB - The reconstruction of missing data in image time series due to cloud masking, among other reasons, is addressed in this paper. A new patch-based strategy based on the similarities between the spatial, spectral and temporal evolutions of the image pixel values is proposed. Experiments are carried out using Landsat-8 and SPOT-5 image time series. The proposed methodology is compared to classical temporal interpolation approaches.

KW - Cloud removal

KW - High resolution

KW - image reconstruction

KW - Satellite Image Time Series

UR - https://www.scopus.com/pages/publications/85007507976

U2 - 10.1109/IGARSS.2016.7729596

DO - 10.1109/IGARSS.2016.7729596

M3 - Conference Paper

AN - SCOPUS:85007507976

SN - 9781509033331

SP - 2308

EP - 2311

BT - 2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings

A2 - Shi, Jiancheng

A2 - Guo, Huadong

A2 - Chen, Kun-shan

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - IEEE International Geoscience and Remote Sensing Symposium 2015

Y2 - 26 July 2015 through 31 July 2015

ER -

Valero S, Pelletier C, Bertolino M. Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities. In Shi J, Guo H, Chen K, editors, 2016 IEEE International Geoscience & Remote Sensing Symposium - Proceedings: July 10–15, 2016 Beijing, China. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2016. p. 2308-2311. 7729596 doi: 10.1109/IGARSS.2016.7729596

Patch-based reconstruction of high resolution satellite image time series with missing values using spatial, spectral and temporal similarities

Abstract

Conference

Keywords

Access to Document

Other files and links

Cite this