A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space

JI Jian; LYU Xiaojia; YAO Yafeng

doi:10.1049/cje.2017.06.018

Volume 26 Issue 4

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Article Navigation > Chinese Journal of Electronics > 2017 > 26(4): 883-888

JI Jian, LYU Xiaojia, YAO Yafeng, “A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space,” Chinese Journal of Electronics, vol. 26, no. 4, pp. 883-888, 2017, doi: 10.1049/cje.2017.06.018

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JI Jian, LYU Xiaojia, YAO Yafeng, “A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space,” Chinese Journal of Electronics, vol. 26, no. 4, pp. 883-888, 2017, doi: 10.1049/cje.2017.06.018

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A SAR Image Segment Method Using Gray Level Reduction Based on Graph in ICA Space

doi: 10.1049/cje.2017.06.018

1.
School of Computer Science and Technology, Xidian University, Xi'an 717001, China;
2.
Netease Group, Hangzhou, 310000, China

Funds: This work was supported by the Fundamental Research Funds for the Central Universities of China (No.160302).

Received Date: 2015-06-22
Rev Recd Date: 2016-07-21
Publish Date: 2017-07-10

Abstract

Abstract

This paper proposes a new SAR image segmentation method based on graph and gray level reduction in Independent component analysis (ICA) space. Firstly, according to the grayscale information of SAR image, effective use of gray level reduction for initial segmentation can group the pixels with same or similar values to the same homogeneous region, which can address the problem of over-segmentation. Secondly, the features of regions are extracted in ICA space, and then the similarity degree can be calculated by Euclidean distance. The initial regions are merged in fully connected graph based on minimum spanning tree in ICA space. The process of region merging is divided into two phases; the first phrase is merging the different regions with the largest similarity degree, the second will focus on updating the fully connected graph for iteration. Finally, experimental and comparative results on synthetic and real SAR images verify the efficiency of the proposed algorithm.
- SAR image segmentation,
- Gray level reduction,
- Independent component analysis (ICA) space,
- Fully connected graph

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References(27)

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