Title :
Weighted Support Vector Machine Segmentation of SAR Images Based on MARMA model
Author :
Wang, Peng-Wei ; Wu, Xiu-Qing ; Yu, Shan
Author_Institution :
Univ. of Sci. & Technol. of China, Hefei
Abstract :
Synthetic aperture radar (SAR) is a coherent sensing device. Existing algorithms for processing optical images are not suitable for SAR images because of speckles noise in SAR images. This paper introduces the support vector machine (SVM) segmentation of SAR images based on multiscale autoregressive moving average (MARMA) model, which can capture the statistical scale-dependency of SAR images. Firstly, the multiscale sequences of SAR image are constructed. Secondly, the paper investigates how to establish MARMA model and how to extract the multiscale stochastic characteristics of the different SAR texture images. Finally, the paper classifies the characteristics vector using generalized weighted SIM. Experiments show that the proposed algorithm is efficient.
Keywords :
autoregressive moving average processes; image sequences; image texture; radar imaging; support vector machines; SAR images; multiscale autoregressive moving average; speckles noise; synthetic aperture radar; weighted support vector machine segmentation; Adaptive optics; Autoregressive processes; Image segmentation; Optical noise; Optical sensors; Speckle; Stochastic processes; Support vector machine classification; Support vector machines; Synthetic aperture radar;
Conference_Titel :
Image and Graphics, 2007. ICIG 2007. Fourth International Conference on
Conference_Location :
Sichuan
Print_ISBN :
0-7695-2929-1
DOI :
10.1109/ICIG.2007.8