Title :
A Novel Statistical Approach for Speckle Filtering of SAR Images
Author :
Amirmazlaghani, Maryam ; Amindavar, Hamidreza
Author_Institution :
Amirkabir Univ. of Technol., Tehran
Abstract :
Synthetic aperture radar (SAR) images are inherently affected by a signal multiplicative noise known as speckle, which is due to the radar wave coherence. In this paper, we introduce a new method to reduce speckle noise in SAR images, based on statistical modeling of wavelet coefficients. We use two-dimensional generalized autoregressive conditional heteroscedasticity (GARCH) model for statistical modeling of images wavelet coefficients. By using this model, we are capable of taking into account important characteristics of wavelet coefficients, such as heavy tailed marginal distribution, and the dependencies between the coefficients. Furthermore, we use maximum a-posteriori (MAP) estimator for estimating the clean image wavelet coefficients. Finally, we compare our proposed method with some denoising methods, and quantify the achieved performance improvement.
Keywords :
filtering theory; maximum likelihood estimation; radar imaging; statistical analysis; synthetic aperture radar; wavelet transforms; SAR images; image denoising methods; images wavelet coefficients; maximum a-posteriori estimator; speckle filtering; statistical approach; synthetic aperture radar images; two-dimensional generalized autoregressive conditional heteroscedasticity; Adaptive filters; Bayesian methods; Earth; Filtering; Image analysis; Noise reduction; Optical noise; Speckle; Synthetic aperture radar; Wavelet coefficients; MAP estimation; Statistical modeling; speckle; synthetic aperture radar;
Conference_Titel :
Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th
Conference_Location :
Marco Island, FL
Print_ISBN :
978-1-4244-3677-4
Electronic_ISBN :
978-1-4244-3677-4
DOI :
10.1109/DSP.2009.4785967