Title :
Bayesian nonlocal means filter for SAR image despeckling
Author :
Zhong, Hua ; Li, Yongwei ; Jiao, Licheng
Author_Institution :
Key Lab. of Intell. Perception & Image Understanding, Xidian Univ., Xi´´an, China
Abstract :
The nonlocal (NL) means filter as a recent denoising approach has demonstrated its empirical merit for additive Gaussian noise. In this paper, a novel Bayesian nonlocal (BNL) means filter is derived, which is adapted to the multiplicative speckle noise. The new filter is better parameterized using the Bayesian framework, in which a new statistical distance is introduced to measure the similarity of speckled patches. The proposed method is validated on real synthetic aperture radar (SAR) images through comparisons with other classical despeckling methods.
Keywords :
AWGN; belief networks; radar imaging; synthetic aperture radar; Bayesian nonlocal means filter; SAR image despeckling; additive Gaussian noise; multiplicative speckle noise; statistical distance; Additive noise; Bayesian methods; Equations; Gaussian noise; Information filtering; Information filters; Noise reduction; Pixel; Speckle; Synthetic aperture radar; Bayesian; NL means; SAR; despeckling;
Conference_Titel :
Synthetic Aperture Radar, 2009. APSAR 2009. 2nd Asian-Pacific Conference on
Conference_Location :
Xian, Shanxi
Print_ISBN :
978-1-4244-2731-4
Electronic_ISBN :
978-1-4244-2732-1
DOI :
10.1109/APSAR.2009.5374145