SAR Image Segmentation Combined Regular Tessellation and M-H Algorithm

WANG Yu; LI Yu; ZHAO Quanhua

doi:10.13203/j.whugis20140536

Volume 41 Issue 11

Nov. 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(11): 1491-1497. > DOI: 10.13203/j.whugis20140536

WANG Yu, LI Yu, ZHAO Quanhua. SAR Image Segmentation Combined Regular Tessellation and M-H Algorithm[J]. Geomatics and Information Science of Wuhan University, 2016, 41(11): 1491-1497. DOI: 10.13203/j.whugis20140536

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SAR Image Segmentation Combined Regular Tessellation and M-H Algorithm

WANG Yu^1,,
LI Yu^1, ,,
ZHAO Quanhua¹

1.
Institute for Remote Sensing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin 123000, China

Funds:

The National Natural Science Foundation of China 41301479

The National Natural Science Foundation of China 41271435

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Author Bio:
WANG Yu, PhD candidate, specializes in image processing. E-mail:1009059221@qq.com
Corresponding author:
LI Yu, PhD, professor. E-mail:lntuliyu@163.com
Received Date: September 06, 2015
Published Date: November 04, 2016

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Abstract

Abstract

This paper presents a SAR image segmentation method that combines regular tessellation and the Metropolis-Hastings (M-H) algorithm. First the image domain is partitioned into a group of rectangular sub-blocks by regular tessellation and then the image is modeled on the assumption that intensities of its pixels in each homogeneous region follow an identical and independent Gamma distribution. A region-based SAR image segmentation model is built using the Bayesian paradigm. Then, an M-H scheme is used to simulate the segmentation model, which can segment SAR image and estimate the model parameters. In the M-H algorithm, three move types are designated, including updating parameter vector, updating label field, and splitting or merging sub-block. The results obtained from both real and simulated SAR images show that the proposed algorithm works effectively and efficiently.
- SAR image segmentation,
- regular tessellation,
- Metropolis-Hastings algorithm

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References (15)

References

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