Title :
SAR Image Filtering Based on the Cauchy–Rayleigh Mixture Model
Author :
Qiangqiang Peng ; Long Zhao
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
Abstract :
In this letter, a novel maximum a posteriori (MAP) filter for synthetic aperture radar (SAR) images is developed. We characterize the return signal of SAR using the Cauchy-Rayleigh mixture model, which is an approximation to the heavy-tailed Rayleigh distribution. The parameters of the Cauchy-Rayleigh mixture model are estimated from the noisy observation by using the expectation-maximization algorithm. Finally, we compare the proposed filter with several classical spatial filtering techniques by applying them on simulated data and various real SAR images. Experimental results show that the Cauchy-Rayleigh-mixture-based MAP filter performs better for speckle removal than the other methods, including Lee, Kuan, and Γ-MAP.
Keywords :
expectation-maximisation algorithm; radar imaging; synthetic aperture radar; Cauchy-Rayleigh mixture based MAP filter; Cauchy-Rayleigh mixture model; Rayleigh distribution; SAR image filtering; expectation-maximization algorithm; maximum a posteriori filter; real SAR images; simulated data; spatial filtering; speckle removal; synthetic aperture radar; Backscatter; Bayes methods; Filtering; Noise; Remote sensing; Speckle; Synthetic aperture radar; Mixture model; spatial filtering; speckle; synthetic aperture radar (SAR) image;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2013.2283258