Special Section on Sparsity-Driven High Dimensional Remote Sensing Image Processing and Analysis

1/2-norm regularized nonnegative low-rank and sparse affinity graph for remote sensing image segmentation

[+] Author Affiliations
Shu Tian, Ye Zhang, Yiming Yan, Nan Su

Harbin Institute of Technology, School of Electronics and Information Technology, Xidazhi Street, Nangang District, Harbin 15000, China

J. Appl. Remote Sens. 10(4), 042008 (Aug 01, 2016). doi:10.1117/1.JRS.10.042008
History: Received February 15, 2016; Accepted July 7, 2016
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Abstract.  Segmentation of real-world remote sensing images is a challenge due to the complex texture information with high heterogeneity. Thus, graph-based image segmentation methods have been attracting great attention in the field of remote sensing. However, most of the traditional graph-based approaches fail to capture the intrinsic structure of the feature space and are sensitive to noises. A 1/2-norm regularization-based graph segmentation method is proposed to segment remote sensing images. First, we use the occlusion of the random texture model (ORTM) to extract the local histogram features. Then, a 1/2-norm regularized low-rank and sparse representation (L1/2NNLRS) is implemented to construct a 1/2-regularized nonnegative low-rank and sparse graph (L1/2NNLRS-graph), by the union of feature subspaces. Moreover, the L1/2NNLRS-graph has a high ability to discriminate the manifold intrinsic structure of highly homogeneous texture information. Meanwhile, the L1/2NNLRS representation takes advantage of the low-rank and sparse characteristics to remove the noises and corrupted data. Last, we introduce the L1/2NNLRS-graph into the graph regularization nonnegative matrix factorization to enhance the segmentation accuracy. The experimental results using remote sensing images show that when compared to five state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Shu Tian ; Ye Zhang ; Yiming Yan and Nan Su
"ℓ1/2-norm regularized nonnegative low-rank and sparse affinity graph for remote sensing image segmentation", J. Appl. Remote Sens. 10(4), 042008 (Aug 01, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.042008


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