Title :
SAR Image Segmentation Using GHM-Based Dirichlet Process Mixture Models
Author :
Sun, Li ; Zhang, Yanning ; Tian, Guangjian ; Ma, Miao
Author_Institution :
Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
This paper proposes a robust SAR image segmentation scheme for SAR images with speckle noise. Our method can simulate the intrinsic property of SAR image by the proposed infinite mixture model-Dirichlet process mixture model and determine the cluster number automatically. The Gaussian-Hermite moment is applied to extract features to improve the robust of segmentation and reduce the influence of speckle noise. The effectiveness of proposed method is demonstrated via experiments with the simulated data and real data.
Keywords :
feature extraction; image segmentation; radar computing; radar imaging; speckle; synthetic aperture radar; Dirichlet process mixture models; GHM; Gaussian-Hermite moment; SAR; feature extraction; image segmentation; infinite mixture model; speckle noise; Clustering algorithms; Computational modeling; Feature extraction; Gaussian noise; Gaussian processes; Image segmentation; Noise reduction; Noise robustness; Polynomials; Speckle; Dirichlet Process; Gaussian Hermite moment; SAR image segmentation;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.371
