Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

Jinchang Ren; Byongjun Hwang; Paul Murray; Soumitra Sakhalkar; Samuel McCormack

doi:10.1109/IGARSS.2015.7325947

Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

Jinchang Ren, Byongjun Hwang, Paul Murray, Soumitra Sakhalkar, Samuel McCormack

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

14 Citations (Scopus)

154 Downloads (Pure)

Abstract

Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includes edge-preserved filtering for pre-processing, k-means clustering for segmentation and conditional morphology filtering for post-processing. As such, the effect of noise has been suppressed and the under-segmented regions are successfully corrected.

Original language	English
Title of host publication	2015 IEEE International Geoscience and Remote Sensing Symposium
Place of Publication	Piscataway, NJ.
Publisher	IEEE
Pages	1040-1043
Number of pages	4
ISBN (Print)	9781479979295
DOIs	https://doi.org/10.1109/IGARSS.2015.7325947
Publication status	Published - 31 Jul 2015
Event	IEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015) - Convention Center, Milan, Italy Duration: 26 Jul 2015 → 31 Jul 2015

Conference

Conference	IEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015)
Abbreviated title	IGARSS 2015
Country/Territory	Italy
City	Milan
Period	26/07/15 → 31/07/15

Keywords

sea ice image segmentation
satellite synthetic aperture radar
edge-preserved filtering
k-means clustering
conditional morphology filtering
remote sensing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/IGARSS.2015.7325947

Ren-etal-IEEE-IGRSS-2015-Effective-SAR-sea-lice-image-segmentation-and-touch-floe-separationAccepted author manuscript, 2.01 MB

Cite this

@inproceedings{2dcdacc183ba40ee82622598e41fa848,

title = "Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach",

abstract = "Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includes edge-preserved filtering for pre-processing, k-means clustering for segmentation and conditional morphology filtering for post-processing. As such, the effect of noise has been suppressed and the under-segmented regions are successfully corrected.",

keywords = "sea ice image segmentation, satellite synthetic aperture radar, edge-preserved filtering, k-means clustering, conditional morphology filtering, remote sensing",

author = "Jinchang Ren and Byongjun Hwang and Paul Murray and Soumitra Sakhalkar and Samuel McCormack",

note = "{\textcopyright} 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; IEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015), IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",

year = "2015",

month = jul,

day = "31",

doi = "10.1109/IGARSS.2015.7325947",

language = "English",

isbn = "9781479979295",

pages = "1040--1043",

booktitle = "2015 IEEE International Geoscience and Remote Sensing Symposium",

publisher = "IEEE",

}

Ren, J, Hwang, B, Murray, P, Sakhalkar, S & McCormack, S 2015, Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach. in 2015 IEEE International Geoscience and Remote Sensing Symposium., 7325947, IEEE, Piscataway, NJ., pp. 1040-1043, IEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015), Milan, Italy, 26/07/15. https://doi.org/10.1109/IGARSS.2015.7325947

TY - GEN

T1 - Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

AU - Ren, Jinchang

AU - Hwang, Byongjun

AU - Murray, Paul

AU - Sakhalkar, Soumitra

AU - McCormack, Samuel

N1 - © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2015/7/31

Y1 - 2015/7/31

N2 - Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includes edge-preserved filtering for pre-processing, k-means clustering for segmentation and conditional morphology filtering for post-processing. As such, the effect of noise has been suppressed and the under-segmented regions are successfully corrected.

AB - Accurate sea-ice segmentation from satellite synthetic aperture radar (SAR) images plays an important role for understanding the interactions between sea-ice, ocean and atmosphere in the Arctic. Processing sea-ice SAR images are challenging due to poor spatial resolution and severe speckle noise. In this paper, we present a multi-stage method for the sea-ice SAR image segmentation, which includes edge-preserved filtering for pre-processing, k-means clustering for segmentation and conditional morphology filtering for post-processing. As such, the effect of noise has been suppressed and the under-segmented regions are successfully corrected.

KW - sea ice image segmentation

KW - satellite synthetic aperture radar

KW - edge-preserved filtering

KW - k-means clustering

KW - conditional morphology filtering

KW - remote sensing

UR - http://ieeexplore.ieee.org/Xplore/home.jsp

UR - http://www.igarss2015.org/

UR - http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7303999

U2 - 10.1109/IGARSS.2015.7325947

DO - 10.1109/IGARSS.2015.7325947

M3 - Conference contribution book

SN - 9781479979295

SP - 1040

EP - 1043

BT - 2015 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

CY - Piscataway, NJ.

T2 - IEEE International Geoscience and Remote Sensing Sympium (IGARSS 2015)

Y2 - 26 July 2015 through 31 July 2015

ER -

Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Enhancing international collaborations for the retrieval of sea ice floe size distribution distribution (FSD) from satellite SAR imagery

New image analysis technologies for fast and accurate retrieval of sea ice floe size distribution (FSD) from satellite SAR imagery

New image analysis for the retrieval of sea ice floe size from satellite SAR imagery

Cite this

Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach

Abstract

Conference

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Projects

Enhancing international collaborations for the retrieval of sea ice floe size distribution distribution (FSD) from satellite SAR imagery

New image analysis technologies for fast and accurate retrieval of sea ice floe size distribution (FSD) from satellite SAR imagery

New image analysis for the retrieval of sea ice floe size from satellite SAR imagery

Cite this