A Novel Algorithm of Water Region Detection in SAR Image Based on Bag of Visual Words and Local Pattern Histogram

FENG Jing; CHEN Liang; WEI Hang; BI Fukun; CHEN He

doi:10.1049/cje.2016.08.019

Volume 25 Issue 5

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FENG Jing, CHEN Liang, WEI Hang, et al., “A Novel Algorithm of Water Region Detection in SAR Image Based on Bag of Visual Words and Local Pattern Histogram,” Chinese Journal of Electronics, vol. 25, no. 5, pp. 974-979, 2016, doi: 10.1049/cje.2016.08.019

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FENG Jing, CHEN Liang, WEI Hang, et al., “A Novel Algorithm of Water Region Detection in SAR Image Based on Bag of Visual Words and Local Pattern Histogram,” Chinese Journal of Electronics, vol. 25, no. 5, pp. 974-979, 2016, doi: 10.1049/cje.2016.08.019

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A Novel Algorithm of Water Region Detection in SAR Image Based on Bag of Visual Words and Local Pattern Histogram

doi: 10.1049/cje.2016.08.019

1.
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China;
2.
College of Information Engineering, North China University of Technology, Beijing 100144, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61171194).

More Information

Corresponding author: CHEN Liang (corresponding author) was born in Shijiazhuang, Hebei Province, China, in 1981. He got his Ph.D. degree in Beijing Institute of Technology, China, in 2008. Currently, he is a faculty member at School of Information and Electronics, Beijing Institute of Technology. His research interests include real-time signal processing, remote sensing images processing, and object detection and recognition. (Email:chenl@bit.edu.cn)
Received Date: 2014-07-18
Rev Recd Date: 2015-02-16
Publish Date: 2016-09-10

Abstract

Abstract

Water region detection based on SAR images is a difficult problem for its computing complexity. This paper proposes a novel water region detection method in SAR image of complex scenery. The algorithm takes advantages of Bag of visual words (BOV) to precisely describe the homogeneous region in complex scenery. Local pattern histogram (LPH) and single-class Support vector machine (SVM) are adopted to determine the edge information of water region precisely. The feature extraction is calculated block by block, which reduces computing workload and interference from noise. The experiments based on SAR images of real complex scenery show that the proposed method achieves higher accuracy and robustness.
- Synthetic aperture radar (SAR),
- Water region detection,
- Bag of visual words (BOV),
- Local pattern histogram (LPH),
- Single-class support vector machine (SVM)

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References(17)

References

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