A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation

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A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation. / Shang, Ronghua; Chen, Chen; Wang, Guangguang; Jiao, Licheng; Okoth, Michael Aggrey; Stolkin, Rustam.

In: Signal Processing, Vol. 171, 107518, 06.2020, p. 1-15.

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Shang, Ronghua ; Chen, Chen ; Wang, Guangguang ; Jiao, Licheng ; Okoth, Michael Aggrey ; Stolkin, Rustam. / A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation. In: Signal Processing. 2020 ; Vol. 171. pp. 1-15.

Bibtex

@article{dd7fe1182c034a97bad210f04b553f0b,
title = "A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation",
abstract = "This paper proposes a novel algorithm for segmentation of synthetic aperture radar (SAR) image, our proposed algorithm (THFCM) is based on thumbnail representations and a hierarchical fuzzy C-means (FCM) approach. THFCM firstly divides the image into pixel groups to extract local feature, and the major pixels of each pixel group are selected to construct a thumbnail. FCM is then used to segment each thumbnail, and hierarchical segmentation is then performed on the overall image data, based on the results of thumbnail clustering. The thumbnail approach leverages local image information, helping to overcome speckle noise, while the hierarchical approach improves computational efficiency. Experiments on simulated and real SAR images suggest that THFCM outperforms several other state-of-the-art algorithms in terms of both segmentation accuracy and running time.",
author = "Ronghua Shang and Chen Chen and Guangguang Wang and Licheng Jiao and Okoth, {Michael Aggrey} and Rustam Stolkin",
year = "2020",
month = jun,
doi = "10.1016/j.sigpro.2020.107518",
language = "English",
volume = "171",
pages = "1--15",
journal = "Signal Processing",
issn = "0165-1684",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation

AU - Shang, Ronghua

AU - Chen, Chen

AU - Wang, Guangguang

AU - Jiao, Licheng

AU - Okoth, Michael Aggrey

AU - Stolkin, Rustam

PY - 2020/6

Y1 - 2020/6

N2 - This paper proposes a novel algorithm for segmentation of synthetic aperture radar (SAR) image, our proposed algorithm (THFCM) is based on thumbnail representations and a hierarchical fuzzy C-means (FCM) approach. THFCM firstly divides the image into pixel groups to extract local feature, and the major pixels of each pixel group are selected to construct a thumbnail. FCM is then used to segment each thumbnail, and hierarchical segmentation is then performed on the overall image data, based on the results of thumbnail clustering. The thumbnail approach leverages local image information, helping to overcome speckle noise, while the hierarchical approach improves computational efficiency. Experiments on simulated and real SAR images suggest that THFCM outperforms several other state-of-the-art algorithms in terms of both segmentation accuracy and running time.

AB - This paper proposes a novel algorithm for segmentation of synthetic aperture radar (SAR) image, our proposed algorithm (THFCM) is based on thumbnail representations and a hierarchical fuzzy C-means (FCM) approach. THFCM firstly divides the image into pixel groups to extract local feature, and the major pixels of each pixel group are selected to construct a thumbnail. FCM is then used to segment each thumbnail, and hierarchical segmentation is then performed on the overall image data, based on the results of thumbnail clustering. The thumbnail approach leverages local image information, helping to overcome speckle noise, while the hierarchical approach improves computational efficiency. Experiments on simulated and real SAR images suggest that THFCM outperforms several other state-of-the-art algorithms in terms of both segmentation accuracy and running time.

U2 - 10.1016/j.sigpro.2020.107518

DO - 10.1016/j.sigpro.2020.107518

M3 - Article

VL - 171

SP - 1

EP - 15

JO - Signal Processing

JF - Signal Processing

SN - 0165-1684

M1 - 107518

ER -